Intro

  There is a saying that the novice will write code that works, without thinking of anything else, the expert will come and rewrite that code according to good practices and the master will rewrite it so that it works again, thinking of everything. It applies particularly well to SQL. Sometimes good and well tried best practices fail in specific cases and one must guide themselves either by precise measurements of by narrow rules that take decades to learn.

  If you ever wondered why some SQL queries are very slow or how to write complex SQL stored procedures without them reaching sentience and behaving unpredictably, this post might help. I am not a master myself, but I will share some quick and dirty ways of writing, then checking your SQL code.

Some master rules

  First of all, some debunking of best practices that make unreasonable assumptions at scale:

  1. If you have to extract data based on many parameters, then add them as WHERE or ON clauses and the SQL engine will know how to handle it.

    For small queries and for well designed databases, that is correct. The SQL server engine is attempting to create execution plans for these parameter combinations and reuse them in the future on other executions. However, when the number of parameters increases, the number of possible parameter combinations increases exponentially. The execution optimization should not take more than the execution itself, so the engine if just choosing one of the existing plans which appears more similar to the parameters given. Sometimes this results in an abysmal performance.

    There are two solutions:

    The quick and dirty one is to add OPTION (RECOMPILE) to the parameterized SELECT query. This will tell the engine to always ignore existing execution plans. With SQL 2016 there is a new feature called Query Store plus a graphical interface that explores execution plans, so one can choose which ones are good and which ones are bad. If you have the option, you might manually force an execution plan on specific queries, as well. But I don't recommend this because it is a brittle and nonintuitive solution. You need a DBA to make sure the associations are correct and maintained properly.

    The better one, to my own surprise, is to use dynamic SQL. In other words, if you have 20 parameters to your stored procedure, with only some getting used at any time (think an Advanced Search page), create an SQL string only with the parameters that are set, then execute it.

    My assumption has always been that the SQL engine will do this for me if I use queries like WHERE (@param IS NULL OR <some condition with @param>). I was disappointed to learn that it does not always do that. Be warned, though, that most of the time multiple query parameters are optimized by running several operations in parallel, which is best!

  2. If you query on a column or another column, an OR clause will be optimal. 

    Think of something like this: You have a table with two account columns AccId and AccId2. You want to query a lot on an account parameter @accountId and you have added an index on each column.

    At this time the more readable option, and for small queries readability is always preferable to performance improvement, is WHERE AccId=@accountId OR AccId2=@accountId. But how would the indexes be used here, in this OR clause? First the engine will have to find all entries with the correct AccId, then again find entries with the correct AccId2, but only the entries that have not been found in the first search.

    First of all, SQL will not do this very well when the WHERE clause is very complex. Second of all, even if it did it perfectly, if you know there is no overlap, or you don't care or you can use a DISTINCT further on to eliminate duplicates, then it is more effective to have two SELECT queries, one for AccId and the other for AccId2 that you UNION ALL afterwards.

    My assumption has always been that the SQL engine will do this automatically. I was quite astounded to hear it was not true. Also, I may be wrong, because different SQL engines and their multitude of versions, compounded with the vast array of configuration options for both engine and any database, behave quite differently. Remember the parallelism optimization, as well.

  3. Temporary tables as slow, use table variables instead.

    Now that is just simple logic, right? A temporary table uses disk while a table variable uses memory. The second has to be faster, right? In the vast majority of cases this will be true. It all depends (a verb used a lot in SQL circles) on what you do with it.

    Using a temporary table might first of all be optimized by the engine to not use the disk at all. Second, temporary tables have statistics, while table variables do not. If you want the SQL engine to do its magic without your input, you might just have to use a temporary table.

  4. A large query that does everything is better than small queries that I combine later on.

    This is a more common misconception than the others. The optimizations the SQL engine does work best on smaller queries, as I've already discussed above, so if a large query can be split into two simpler ones, the engine will be more likely able to find the best way of executing each. However, this only applies if the two queries are completely independent. If they are related, the engine might find the perfect way of getting the data in a query that combines them all.

    Again, it depends. One other scenario is when you try to DELETE or UPDATE a lot of rows. SQL is always "logging" the changes that it does on the off chance that the user cancels the query and whatever incomplete work has been done has to be undone. With large amounts of data, this results into large log files and slow performance. One common solution is to do it in batches, using UPDATE (TOP 10000) or something similar inside a WHILE loop. Note that while this solves the log performance issue, it adds a little bit of overhead for each executed UPDATE

  5. If I have an index on a DATETIME column and I want to check the records in a certain day, I can use CAST or CONVERT.

    That is just a bonus rule, but I've met the problem recently. The general rule is that you should never perform calculations on columns inside WHERE clauses. So instead of WHERE CAST(DateColumn as DATE)=@date use WHERE DateColumn>=@date AND DateColumn<DATEADD(DAY,1,@date). The calculation is done (once) on the parameters given to the query, not on every value of DateColumn. Also, indexes are now used.

Optimizing queries for dummies

So how does one determine if one of these rules apply to their case? "Complex query" might mean anything. Executing a query multiple times results in very different results based on how the engine is caching the data or computing execution plans.

A lot of what I am going to say can be performed using SQL commands, as well. Someone might want to use direct commands inside their own tool to monitor and manage performance of SQL queries. But what I am going to show you uses the SQL Management Studio and, better still, not that horrid Execution Plan chart that often crashes SSMS and it is hard to visualize for anything that the most simple queries. Downside? You will need SQL Management Studio 2014 or higher.

There are two buttons in the SSMS menu. One is "Include Actual Execution Plan" which generates an ugly and sometimes broken chart of the execution. The other one is "Include Live Query Statistics" which seems to be doing the same, only in real time. However, the magic happens when both are enabled. In the Results tab you will get not only the query results, but also tabular data about the execution performance. It is amazingly useful, as you get a table per each intermediary query, for example if you have a stored procedure that executes several queries in a row, you get a table for each.

Even more importantly, it seems that using these options will start the execution without any cached data or execution plans. Running it several times gives consistent execution times.

In the LiveQuery tables, the values we are interested about are, in order of importance, EstimateIO, EstimateCPU and Rows.

EstimateIO is telling us how much of the disk was used. The disk is the slowest part of a computer, especially when multiple processes are running queries at the same time. Your objective is to minimize that value. Luckily, on the same row, we get data about the substatement that generated that row, which parameters were used, which index was used etc. This blog is not about how to fix every single scenario, but only on how to determine where the biggest problems lie.

EstimateCPU is saying how much processing power was used. Most of the time this is very small, as complex calculations should not be performed in queries anyway, but sometimes a large value here shows a fault in the design of the query.

Finally, Rows. It is best to minimize the value here, too, but it is not always possible. For example a COUNT(*) will show a Clustered Index Scan with Rows equal to the row count in the table. That doesn't cause any performance problems. However, if your query is supposed to get 100 rows and somewhere in the Live Query table there is a value of several millions, you might have used a join without the correct ON clause parameters or something like that.

Demo

Let's see some examples of this. I have a Main table, with columns ID BIGINT, Random1 INT, Random2 NVARCHAR(100) and Random3 CHAR(10) with one million rows. Then an Ind table, with columns ID BIGINT, Qfr CHAR(4) and ValInd BIGINT with 10000 rows. The ID table is common with the Main table ID column and the Qfr column has only three possible values: AMT, QTY, Sum.

Here is a demo on how this would work:

DECLARE @r1 INT = 1300000
DECLARE @r2 NVARCHAR(100) = 'a'
DECLARE @r3 CHAR(10) = 'A'
DECLARE @qfr CHAR(4) = 'AMT'
DECLARE @val BIGINT = 500000

DECLARE @r1e INT = 1600000
DECLARE @r2e NVARCHAR(100) = 'z'
DECLARE @r3e CHAR(10)='Z'
DECLARE @vale BIGINT = 600000

SELECT *
FROM Main m
INNER JOIN Ind i
ON m.ID=i.ID
WHERE (@r1 IS NULL OR m.Random1>=@r1)
  AND (@r2 IS NULL OR m.Random2>=@r2)
  AND (@r3 IS NULL OR m.Random3>=@r3)
  AND (@val IS NULL OR i.ValInd>=@val)
  AND (@r1e IS NULL OR m.Random1<=@r1e)
  AND (@r2e IS NULL OR m.Random2<=@r2e)
  AND (@r3e IS NULL OR m.Random3<=@r3e)
  AND (@vale IS NULL OR i.ValInd<=@vale)
  AND (@qfr IS NULL OR i.Qfr=@qfr)

I have used 9 parameters, each with their own values, to limit the number of rows I get. The Live Query result is:

You can see that the EstimateIO values are non-zero only on the Clustered Index Scans, one for each table. Where is how the StmtText looks like: "|--Clustered Index Scan(OBJECT:([Test].[dbo].[Ind].[PK__Ind__DEBF89006F996CA8] AS [i]),  WHERE:(([@val] IS NULL OR [Test].[dbo].[Ind].[ValInd] as [i].[ValInd]>=[@val]) AND ([@vale] IS NULL OR [Test].[dbo].[Ind].[ValInd] as [i].[ValInd]<=[@vale]) AND ([@qfr] IS NULL OR [Test].[dbo].[Ind].[Qfr] as [i].[Qfr]=[@qfr])) ORDERED FORWARD)".

This is a silly case, but you can see that the @parameter IS NULL type of query condition has not been removed, even when parameter is clearly not null.

Let's change the values of the parameters:

DECLARE @r1 INT = 300000
DECLARE @r2 NVARCHAR(100) = NULL
DECLARE @r3 CHAR(10) = NULL
DECLARE @qfr CHAR(4) = NULL
DECLARE @val BIGINT = NULL

DECLARE @r1e INT = 600000
DECLARE @r2e NVARCHAR(100) = NULL
DECLARE @r3e CHAR(10)=NULL
DECLARE @vale BIGINT = NULL

Now the Live Query result is:

Same thing! 5.0 and 7.2

Now, let's do the same thing with dynamic SQL. It's a little more annoying, mostly because of the parameter syntax, but check it out:

DECLARE @sql NVARCHAR(Max)

DECLARE @r1 INT = 300000
DECLARE @r2 NVARCHAR(100) = NULL
DECLARE @r3 CHAR(10) = NULL
DECLARE @qfr CHAR(4) = NULL
DECLARE @val BIGINT = NULL

DECLARE @r1e INT = 600000
DECLARE @r2e NVARCHAR(100) = NULL
DECLARE @r3e CHAR(10)=NULL
DECLARE @vale BIGINT = NULL


SET @sql=N'
SELECT *
FROM Main m
INNER JOIN Ind i
ON m.ID=i.ID
WHERE 1=1 '
IF @r1 IS NOT NULL SET @sql+=' AND m.Random1>=@r1'
IF @r2 IS NOT NULL SET @sql+=' AND m.Random2>=@r2'
IF @r3 IS NOT NULL SET @sql+=' AND m.Random3>=@r3'
IF @val IS NOT NULL SET @sql+=' AND i.ValInd>=@val'
IF @r1e IS NOT NULL SET @sql+=' AND m.Random1<=@r1e'
IF @r2e IS NOT NULL SET @sql+=' AND m.Random2<=@r2e'
IF @r3e IS NOT NULL SET @sql+=' AND m.Random3<=@r3e'
IF @qfr IS NOT NULL SET @sql+=' AND i.Qfr=@qfr'
IF @vale IS NOT NULL SET @sql+=' AND i.ValInd<=@vale'

PRINT @sql

EXEC sp_executesql @sql,
  N'@r1 INT, @r2 NVARCHAR(100), @r3 CHAR(10), @qfr CHAR(4),@val BIGINT,@r1e INT, @r2e NVARCHAR(100), @r3e CHAR(10),@vale BIGINT',
  @r1,@r2,@r3,@qfr,@val,@r1e,@r2e,@r3e,@vale

Now the Live Query results are:

At first glance we have not changed much. IO is still 5.0 and 7.2. Yet there are 3 less execution steps. There is no parallelism and the query has been executed in 5 seconds, not 6. The StmtText for the same thing is now: "|--Clustered Index Scan(OBJECT:([Test].[dbo].[Ind].[PK__Ind__DEBF89006F996CA8] AS [i]), ORDERED FORWARD)". The printed SQL command is:

SELECT *
FROM Main m
INNER JOIN Ind i
ON m.ID=i.ID
WHERE 1=1  AND m.Random1>=@r1 AND m.Random1<=@r1e

Conclusion

Again, this is a silly example. But with some results anyway! In my work I have used this to get a stored procedure to work three to four times faster!

One can optimize usage of IO, CPU and Rows by adding indexes, by narrowing join conditions, by reducing the complexity of executed queries, eliminating temporary tables, partitioning existing tables, adding or removing hints, removing computation from queried columns and so many other possible methods, but they amount to nothing if you cannot measure the results of your changes.

By using Actual Execution Plan together with Live Query Statistics you get:

  • consistent execution times and disk usage
  • a clear measure of what went on with each subquery

I wish I had some more interesting examples for you, guys, but screenshots from the workplace are not something I want to do and I don't do any complex SQL work at home. I hope this helps. 

  When I was looking at Javascript frameworks like Angular and ReactJS I kept running into these weird reducers that were used in state management mostly. It all felt so unnecessarily complicated, so I didn't look too closely into it. Today, reading some random post on dev.to, I found this simple and concise piece of code that explains it:

// simple to unit test this reducer
function maximum(max, num) { return Math.max(max, num); }

// read as: 'reduce to a maximum' 
let numbers = [5, 10, 7, -1, 2, -8, -12];
let max = numbers.reduce(maximum);

Kudos to David for the code sample.

The reducer, in this case, is a function that can be fed to the the reduce function, which is known to developers in Javascript and a few other languages, but which for .NET developers it's foreign. In LINQ, we have Aggregate!

// simple to unit test this Aggregator ( :) )
Func<int, int, int> maximum = (max, num) => Math.Max(max, num);

// read as: 'reduce to a maximum' 
var numbers = new[] { 5, 10, 7, -1, 2, -8, -12 };
var max = numbers.Aggregate(maximum);

Of course, in C# Math.Max is already a reducer/Aggregator and can be used directly as a parameter to Aggregate.

I found a lot of situations where people used .reduce instead of a normal loop, which is why I almost never use Aggregate, but there are situations where this kind of syntax is very useful. One would be in functional programming or LINQ expressions that then get translated or optimized to something else before execution, like SQL code. (I don't know if Entity Framework translates Aggregate, though). Another would be where you have a bunch of reducers that can be used interchangeably.

Intro

  I want to examine together with you various types of sort algorithms and the tricks they use to lower the magic O number. I reach the conclusion that high performance algorithms that are labeled as specific to a certain type of data can be made generic or that the generic algorithms aren't really that generic either. I end up proposing a new form of function that can be fed to a sorting function in order to reach better performance than the classic O(n*log(n)). Extra bonus: finding distinct values in a list.

Sorting

  But first, what is sorting? Given a list of items that can be compared to one another as lower or higher, return the list in the order from lowest to highest. Since an item can be any type of data record, to define a generic sorting algorithm we need to feed it the rules that make an item lower than another and that is called the comparison function. Let's try an example in Javascript:

  // random function from start to end inclusive
  function rand(start, end) {
    return parseInt(start + Math.random() * (end - start + 1));
  }
  
  // measure time taken by an action and output it in console
  let perfKey = 0;
  function calcPerf(action) {
    const key = perfKey++;
    performance.mark('start_' + key);
    action();
    performance.mark('end_' + key);
    const measure = performance.measure('measure_' + key, 'start_' + key, 'end_' + key);
    console.log('Action took ' + measure.duration);
  }
  
  // change this based on how powerful the computer is
  const size = 10000000;
  // the input is a list of size 'size' containing random values from 1 to 50000
  const input = [];
  for (let i = 0; i < size; i++)
    input.push(rand(1, 50000));
  
  // a comparison function between two items a and b
  function comparisonFunction(a, b) {
    if (a > b)
      return 1;
    if (a < b)
      return -1;
    return 0;
  }
  
  const output = [];
  // copy input into output, then sort it using the comparison function
  // same copying method will be used for future code
  calcPerf(() => {
    for (let i = 0; i < size; i++)
      output.push(input[i]);
    output.sort(comparisonFunction);
  });

  It's not the crispest code in the world, but it's simple to understand:

  • calcPerf is computing the time it takes for an action to take and logs it to the console
  • start by creating a big array of random numbers as input
  • the array in a result array and sorting it with the default sort function, to which we give the comparison function
  • display the time it took for the operation.

  This takes about 4500 milliseconds on my computer.

  Focus on the comparison function. It takes two items and returns a number that is -1, 0 or 1 depending on whether the first item is smaller, equal or larger than the second. Now let's consider the sorting algorithm itself. How does it work?

  A naive way to do it would be to find the smallest item in the list, move it to the first position in the array, then continue the process with the rest of the array. This would have a complexity of O(n2). If you don't know what the O complexity is, don't worry, it just provides an easy to spell approximation of how the amount of work would increase with the number of items in the input. In this case, 10 million records, squared, would lead to 100 trillion operations! That's not good.

  Other algorithms are much better, bringing the complexity to O(n*log(n)), so assuming base 10, around 70 million operations. But how do they improve on this? Surely in order to sort all items you must compare them to each other. The explanation is that if a<b and b<c you do not need to compare a to c. And each algorithm tries to get to this in a different way.

  However, the basic logic of sorting remains the same: compare all items with a subset of the other items.

Partitioning

  A very common and recommended sorting algorithm is QuickSort. I am not going to go through the entire history of sorting algorithms and what they do, you can check that out yourself, but I can focus on the important innovation that QuickSort added: partitioning. The first step in the algorithm is to choose a value out of the list of items, which the algorithm hopes it's as close as possible to the median value and is called a pivot, then arrange the items in two partitions: the ones smaller than the pivot and the ones larger than the pivot. Then it proceeds on doing the same to each partition until the partitions are small enough to be sorted by some other sort algorithm, like insertion sort (used by Chrome by default).

  Let's try to do this manually in our code, just the very first run of the step, to see if it improves the execution time. Lucky for us, we know that the median is around 25000, as the input we generated contains random numbers from 1 to 50000. So let's copy the values from input into two output arrays, then sort each of them. The sorted result would be reading from the first array, then from the second!

  // two output arrays, one for numbers below 25000, the other for the rest
  const output1 = [];
  const output2 = [];
  const pivot = 25000;
  
  calcPerf(() => {
    for (let i = 0; i < size; i++) {
      const val = input[i];
      if (comparisonFunction(val, pivot) < 0)
        output1.push(val);
      else
        output2.push(val);
    }
    // sorting smaller arrays is cheaper
    output1.sort(comparisonFunction);
    output2.sort(comparisonFunction);
  });

  Now, the performance is slightly better. If we do this several times, the time taken would get even lower. The partitioning of the array by an operation that is essentially O(n) (we just go once through the entire input array) reduces the comparisons that will be made in each partition. If we would use the naive sorting, partitioning would reduce nto n+(n/2)2+(n/2)2 (once for each partitioned half), thus n+n2/2. Each partitioning almost halves the number of operations!

  So, how many times can we half the number of operations for? Imagine that we do this with an array of distinct values, from 1 to 10 million. In the end, we would get to partitions of just one element and that means we did a log2(n) number of operations and for each we added one n (the partitioning operation). That means that the total number of operations is... n*log(n). Each algorithm gets to this in a different way, but at the core of it there is some sort of partitioning, that b value that makes comparing a and c unnecessary.

  Note that we treated the sort algorithm as "generic", meaning we fed it a comparison function between any two items, as if we didn't know how to compare numbers. That means we could have used any type of data as long as we knew the rule for comparison between items.

  There are other types of sorting algorithms that only work on specific types of data, though. Some of them claim a complexity of O(n)! But before we get to them, let's make a short detour.

Distinct values

  Another useful operation with lists of items is finding the list of distinct items. From [1,2,2,3] we want to get [1,2,3]. To do this, we often use something called a trie, a tree-like data structure that is used for quickly finding if a value exists or not in a list. It's the thing used for autocorrect or finding a word in a dictionary. It has an O(log n) complexity in checking if an item exists. So in a list of 10 million items, it would take maybe 20 operations to find the item exists or not. That's amazing! You can see that what it does is partition the list down to the item level.

  Unfortunately, this only works for numbers and strings and such primitive values. If we want to make it generic, we need to use a function that determines when two items are equal and then we use it to compare to all the other items we found as distinct so far. That makes using a trie impossible.

  Let me give you an example: we take [1,1,2,3,3,4,5] and we use an externally provided equality function:

  • create an empty output of distinct items
  • take first item (1) and compare with existing distinct items (none)
  • item is not found, so we add it to output
  • take next item (1) and compare with existing distinct items (1)
  • item is found, so we do nothing
  • ...
  • we take the last item (5) and compare with existing items (1,2,3,4)
  • item is not found, so we add it to the output

  The number of operations that must be taken is the number of total items multiplied by the average number of distinct items. That means that for a list of already distinct values, the complexity if O(n2). Not good! It increases exponentially with the number of items. And we cannot use a trie unless we have some function that would provide us with a distinctive primitive value for an item. So instead of an equality function, a hashing function that would return a number or maybe a string.

  However, given the knowledge we have so far, we can reduce the complexity of finding distinct items to O(n*log(n))! It's as simple as sorting the items, then going through the list and sending to output an item when different from the one before. One little problem here: we need a comparison function for sorting, not an equality one.

So far

  We looked into the basic operations of sorting and finding distinct values. To be generic, one has to be provided with a comparison function, the other with an equality function. However, if we would have a comparison function available, finding distinct generic items would become significantly less complex by using sorting. Sorting is better than exponential comparison because it uses partitioning as an optimization trick.

Breaking the n*log(n) barrier

  As I said above, there are algorithms that claim a much better performance than n*log(n). One of them is called RadixSort. BurstSort is a version of it, optimized for strings. CountSort is a similar algorithm, as well. The only problem with Radix type algorithms is that they only work on numbers or recursively on series of numbers. How do they do that? Well, since we know we have numbers to sort, we can use math to partition the lot of them, thus reducing the cost of the partitioning phase.

  Let's look at our starting code. We know that we have numbers from 1 to 50000. We can find that out easily by going once through all of them and computing the minimum and maximum value. O(n). We can then partition the numbers by their value. BurstSort starts with a number of "buckets" or lists, then assigns numbers to the buckets based on their value (dividing the value to the number of buckets). If a bucket becomes too large, it is "burst" into another number of smaller buckets. In our case, we can use CountSort, which simply counts each occurrence of a value in an ordered array. Let's see some code:

  const output = [];
  const buckets = [];
  calcPerf(() => {
    // for each possible value add a counter
    for (let i = 1; i <= 50000; i++)
      buckets.push(0);
    // count all values
    for (let i = 1; i <= size; i++) {
      const val = input[i];
      buckets[val - 1]++;
    }
    // create the output array of sorted values
    for (let i = 1; i <= 50000; i++) {
      const counter = buckets[i - 1];
      for (let j = 0; j < counter; j++)
        output.push(i);
    }
  });

  This does the following:

  • create an array from 1 to 50000 containing zeros
  • for each value in the input, increment the bucket for that value
  • at the end just go through all of the buckets and output the value as many times as the value in the bucket shows

  This algorithm generated a sorted output array in 160 milliseconds!

  And of course, it is too good to be true. We used a lot of a priori knowledge:

  • min/max values were already known
  • the values were conveniently close together integers so we can use them as array indexes

  I can already hear you sigh "Awwh, so I can't use it!". Do not despair yet!

  The Radix algorithm, that is used only for numbers, is also used on strings. How? Well, a string is reducible to a list of numbers (characters) so one can recursively assign each string into a bucket based on the character value at a certain index. Note that we don't have to go through the entire string, the first few letters are enough to partition the list in small enough lists that can be cheaply sorted.

  Do you see it yet?

A generic partition function

  What if we would not use an equality function or a comparison function or a hashing function as a parameter for our generic sort/distinct algorithm? What if we would use a partition function? This partition function would act like a multilevel hashing function returning values that can also be compared to each other. In other words, the generic partition function could look like this:

  function partitionFunction(item, level) returning a byte

  For strings it returns the numeric value of the character at position level or 0. For numbers it returns the high to low byte in the number. For object instances with multiple properties, it would return a byte for each level in each of the properties that we want to order by. Radix style buckets would use the known values from 0 to 255. The fact that the multilevel partitioning function is provided by the user means we can pack in it all the a priori knowledge we have, while keeping the sorting/distinct algorithm unchanged and thus, generic! The sorting will be called by providing two parameters: the partitioning function and the maximum level to which it should be called:

  sort(input, partitioningFunction, maxLevel)

A final example

  Here is an implementation of a radix sorting algorithm that receives a multilevel partitioning function using our original input. Note that it is written so that it is easily read and not for performance:

  // will return a sorted array from the input array
  // using the partitioning function up to maxLevel
  function radixSort(input, partitioningFunction, maxLevel) {
    let buckets = Array.from({length: 256}, () => []);
    buckets[0] = input;
    // reverse order, because level 0 should be the most significant
    for (let level = maxLevel-1; level >=0; level--) {
      let tempBuckets = Array.from({length: 256}, () => []);
      for (let bucketIndex = 0; bucketIndex < buckets.length; bucketIndex++) {
        const bucket = buckets[bucketIndex];
        const bucketLength = bucket.length;
        for (let bucketOffset = 0; bucketOffset < bucketLength; bucketOffset++) {
          const val = bucket[bucketOffset];
          const partByte = partitioningFunction(val, level);
          tempBuckets[partByte].push(val);
        }
      }
      buckets = tempBuckets;
    }
    const output = [].concat(...buckets);
    return output;
  }

  // return value bytes, from the most significant to the least
  // being <50000 the values are always 2 bytes  
  function partitioningFunction(item, level) {
    if (level === 0) return item >> 8;
    if (level === 1) return item & 255;
    return 0;
  }
  
  let output3 = [];
  calcPerf(() => {
    output3 = radixSort(input, partitioningFunction, 2);
  });

Want to know how long it took? 1300 milliseconds!

You can see how the same kind of logic can be used to find distinct values, without actually sorting, just by going through each byte from the partitioning function and using them as values in a trie, right?

Conclusion

Here is how a generic multilevel partitioning function replaces comparison, equality and hashing functions with a single concept that is then used to get high performance from common data operations such as sorting and finding distinct values.

I will want to work on formalizing this and publishing it as a library or something like that, but until then, what do you think?

Wait, there is more

There is a framework in which something similar is being used: SQL. It's the most common place where ORDER BY and DISTINCT are used. In SQL's case, we use an optimization method that uses indexes, which are also trie data structures storing the keys that we want to order or filter by. Gathering the data to fill a database index also has its complexity. In this case, we pre-partition once and we sort many. It's another way of reducing the cost of the partitioning

However, this is just a sub-type of the partition function that I am talking about, one that uses a precomputed data structure to reach its goal. The multilevel partition function concept I am describing here may be pure code or some other encoding of information we know out of hand before doing the operation.

Finally, the complexity. What is it? Well instead of O(n*log(n)) we get O(n*k), where k is the maximum level used in the partition function. This depends on the data, so it's not a constant, but it's the closest theoretical limit for sorting, closer to O(n) than the classic log version. I am not the best algorithm and data structure person, so if you have ideas about it and want to help me out, I would be grateful.  

  Four years ago this day I was blogging about a list of technologies that I wanted to learn or at least explore. It was a very ambitious list, with the idea that I might shame myself into studying at least part of it. Apparently, I am shameless. Anyway, this is a follow-up post on how it all went down. 

.NET Core: MVC, Entity Framework, etc.

  I actually had the opportunity to use ASP.Net Core at my job. I didn't have a lot of it, though, so I just did the usual: start working on something, google the hell out of everything, make it work. I used .NET Core 1 and 2, moved to 3 and now they are just getting out 5. Was it useful? Well, actually no.

  The state of the software industry is in constant flux and while new technologies pop up all the time, there is also a strong force moving the other way, mainly coming from the people that pay for software. Why invest in a new technology when the old one has been working fine for years? Yeah, don't answer that. My point is that while staying current with .NET Core was a boon, I didn't really see a lot of paying customers and employers begging me to do anything with it. In fact, I left my job working on a .NET Framework 4.7 automation project to work on an ASP.Net MVC 4 application written in Visual Basic. So I am learning things that are new to me, but really are very old.

  All I am saying is that there is a paradox of job opportunities for technologies that you are supposed to know and be an expert in, but for which few have had the courage to actually pay before.

  Bottom line: having been familiar with older technology that made .Net Core exist, it was kind of simple for me to get into it, but I am not an expert in it. The fact that software generally moved to the web and that server code is now as slim as it can be also undermines the value of being proficient in it. That is, until you really need to be.

OData and OAuth

  Simply said, nothing on this front. These are mostly related to frontend stuff, to new web facing applications that can be found at a public URL. I have not worked in this field basically since forever.

Typescript, Angular

  Oh, the promise of Typescript: a strongly typed language than compiles to Javascript and can be used to code in using static analysis tools, structured code, clear project boundaries! I had the opportunity to work with it. I did that in a much lesser degree than I should have. Yet the tiny contact with the new language left me disappointed. Because it is a superset of Javascript, it inherits most of its problems, can be easily hacked and the tooling chain is basically the Javascript one.

  I commend Microsoft for even attempting to develop this language and I see that it has become popular indeed. I like C#. I like the vanilla Javascript of old. I dislike the weak hybrid that Typescript seems to be. I may be wrong. Things might evolve in very interesting directions with Typescript. I will wait until then.

  And Angular has also grown in a completely different beast. I thought Angular 1 was great, then they came in with version 2 which was completely different. Now it's 9 or 10 or whatever. I liked the structured projects and how easily data change could be controlled from non-UI code. Yet did it all have to be this complex?

Node.JS, npm, Javascript ES6+, Bower, etc.

  I thought that since I like Javascript, I might enjoy Node.JS. Working with Typescript I had to have contact with npm and at least install Node on the computer. Yet I got more and more disillusioned. A complicated chain of tools that seem to be targeted to a concept of "app" rather than a website, for which you need a completely different set of tools, the numerous changes in the paradigm of Javascript and the systems using it and, frankly, a lack of a real reason for using Javascript when I can use C# made me stop trying to get in on the action on this front. And before I started to understand the Node ecosystem, Deno appeared.

  Personally it feels that Javascript is growing too fast and uncontrolled, like a cancer. The language and tooling need to stabilize and by that I mean cut some of the fat away, not add new things. I loved some of the additions to the standard, like arrow functions, let/const and block scope, nullable and spread operators, iterators and generator functions, but then it just started to get more and more bloated, like trying to absorb every new concept in all of the other languages.

  Bottom line: it is ironic that I am now working in an app that must work on Internet Explorer 11, so I cannot even use the new features of the Javascript standard. And yes, I hate that, but at the same time I can do the job just fine. Food for thought.

Docker

  What a great idea this Docker: just tell the system what kind of setup you need and it creates it for you. It can even create it for you from scratch every single time, in isolation, so you can run your software without having to install all that heavy crap I was just telling you about above. And yet I hated it with a vengeance from the moment I tried to use it. With a clear Linux vibe, it wouldn't even work right on Windows. The images for these pseudo-virtual machines were huge. The use was cumbersome. The tooling reminded me of the good old days when I installed a Slackware distro on any old computer, without X system, of course, and then compiled beta versions of every single software I wanted to use and repeated the process whenever I had an issue.

  For a tool that is supposed to bring consistency and ease of use, it worked really inconsistently and was hard to manage. I understand that maybe all that would have gone away if I invested the effort of understanding the whole concept, but it really felt like going backward instead of forward. One day, perhaps, I will change my mind. As of now, I am just waiting for the person who reinvents Docker and makes it do what it has promised to do: ease my life.

Parallel programming

  Hey, this is actually a plus! I had a lot of opportunities to work with parallel programming, understanding the various pitfalls and going deep in the several types of parallel programming concepts in .NET. Am I a parallel programming guru now? No. But I went through the await/async phase and solved problems at all levels of parallelism. I don't like async/await. It is a good idea, it is great when you start a new project, but to add async/await in existing legacy code is a pain the butt. Inevitably you will want to execute an async method from a sync context, control the order or amount of parallel processing, forget to call an async method with await or trying to run one parallely by not calling it with await on purpose and finding that your scope has been disposed.

  Bottom line: I don't have to like it to use async/await, but I feel (without actually knowing a perfect solution) the design of the feature could have been better. And now they added it to Javascript, too! Anyway, I am comfortable in the area now.

HTML5, Responsive Design, LESS/SASS, ReactJS, new CSS, frontend

  A lot of new stuff to learn for a frontend developer. And how glad I am that I am not it! Again I hit the reality of business requirements vs technology requirements. To learn front end development right now is a full job that you have to do alone, for free and in your spare time. Meanwhile, the projects you are working on are not on the cutting edge, no one wants to change them just to help you learn something and, again, these concepts are mostly for public facing web applications. Maybe even mobile development.

  It does help to know all of this, but it is not a job that I want to do. Frontend is for the young. Can I say that? ReactJS, the few times I looked at it, appeared to me to be a sort of ASP for the browser, with that ugly JSX format that combines code and markup and that complicated state flow mechanism. Angular felt too stuffy and so on. Every time I look into frontend stuff it seems like software for the server side from twenty years before.

  Bottom line: If any web framework appealed to me, that would be VueJS! And no one used it at any of my places of work. It seems a framework dedicated to staying simple and efficient. And while I want to know the concepts in all of this stuff, why would I go deep into this when I need a UI designer for anything with a shape? I will be waiting for the resurgence of simple frameworks using the new features of HTML99 and that do not require to learn an entire new ecosystem to make anything work.

WPF, UWP

  I remember I absolutely loved developing in WPF. The MVVM concept of separating the UI completely from the code controlling it, which is then completely separated from the data models used, was very nice. The complete customizability of the UI without changing the code at all was amazing. The performance, not so much. But did it matter? I thought not. Yet the web obliterated the tech from the development world. I believe it deserves a rebirth.

  That being said, I have done nothing in this direction either. Shame on me.

Deep learning, AI, machine learning

  I really wanted to understand and use artificial intelligence, especially since I did my licence paper on neural networks. I love the new concepts, I've read some of the stuff they came up with and I've even been to some conferences on machine learning. Yet I have not yet found the project that could make it worthwhile. Machine learning and especially deep learning projects require huge amounts of data, while working on the underlying technology requires advanced knowledge of statistics and math, which I do not have.

  It seems to me that I will always be the end user of AI rather than working on building it.

Conclusion

  So there you have it: I worked on .NET Core and parallelism and even microservices, dabbled in Typescript and Angular, created a full on LINQ implementation on Javascript and later Typescript. Meanwhile the world went more and more towards frontend and mobile development and Node and stuff like machine learning. And presently I am working for a bank, coding in VB and using jQuery.

  Strangely, I don't really feel guilty about it. Instead I feel like I am still going on the path of discovery, only more of myself rather than of a particular technology. The more I wait, the more new stuff appears and makes whatever I was dreaming of learning obsolete. I even considered not being a developer anymore, maybe becoming an architect or application designer. When something new appears, the immediate instinct is to check it out, to see what novelties they come up with and to find the problems and then discover solutions, then blog about them. It's a wonderfully addictive game, but after playing it for a while, it just blurs into the same thing over and over again. It's not the technology that matters, but the problems that need fixing. As long as I have problems to fix and I can find the solution, I am happy.

  I ask you, if you got to this point, what is the point of learning any technology, when you don't have the cause, the purpose, the problem that you have to solve? An HR person asked me recently why I keep working where I do. I answered: because they need me.

Intro

  So the requirement is "Write a class that would export data into a CSV format". This would be different from "Write a CSV parser", which I think could be interesting, but not as wildly complex as this. The difference comes from the fact that a CSV parser brings a number of problems for the interviewed person to think about right away, but then it quickly dries up as a source for intelligent debate. A CSV exporter seems much simpler, because the developer controls the output, but it increases in complexity as the interview progresses.

  This post is written from the viewpoint of the interviewer.

Setup

  First of all, you start with the most basic question: Do you know what CSV is? I was going to try this question out on a guy who came interviewing for senior developer and I was excited to see how it would go. He answered he didn't know what CSV was. Bummer! I was incredulous, but then I quickly found out he didn't know much else either. CSV is a text format for exporting a number of unidimensional records. The name comes from Comma Separated Values and might at first glance appear to be a tabular data format, an idea made even more credible by Excel being able to open and export .csv files. But it is not. As the name says, it has values separated by a comma. It might even be just one record. It might be containing multiple records of different types. In some cases, the separator for value and record are not even commas or newline.

  It is important to see how the interviewee explains what CSV is, because it is a concept that looks deceivingly simple. Someone who first considers the complexity of the format before starting writing the code works very differently in a team than someone who throws themselves into the code, confident (or just unrealistically optimistic) that they would solve any problem down the line.

  Some ideas to explore, although it pays off to not bring them up yourself:

  • What data do you need to export: arrays, data tables, list of records?
  • Are the records of the same type?
  • Are there restrictions on the type of record?
  • What separators will there be used? How to escape values that contain chosen separators?
  • Do values have restrictions, like not containing separators?
  • CSV header: do we support that? What does it mean in the context of different types of input? 
  • Text encoding, unicode, non-ASCII characters
  • How to handle null values?
  • Number and date formatting
  • Is there an RFC or a specification document for the CSV export format?

Implementation

  In this particular interview I have chosen that the CSV exporter class will only support an input of IEnumerable<T> (this is .NET speak for a bunch of objects of the same type).

  Give ample opportunities for questions from the person interviewed. This is not a speed test. It is important if the candidate considers by themselves issues like:

  • are the object properties simple types? Like string, long, integer, decimal, double, float, datetime?
  • since the requirement is any T, what about objects that are arrays, or self referencing, or having complex objects as properties?
  • how to extract the values of any object (discussions about .NET reflection or Javascript object property discovery show a lot about the interviewee, especially if they start said discussions)

  Go through the code with the candidate. This shows their ability to develop software. How will they name the class, what signature will they use for export method, how they structure the code and how readable it is.

  At this stage you should have a pretty good idea if the candidate is intelligent, competent and how they handle a complex problem from requirement to implementation.

Dig deeper

  This is the time to ask the questions yourself and see how they react to new information, the knowledge that they should have asked themselves the same questions and the stress of changing their design:

  • are comma and newline the only supported separators?
  • are separators characters or strings?
  • what if an exported value is a string containing a comma?
  • do you support values containing newline?
  • if you use quotes to hold a value containing commas and newlines, what happens if values contain quotes
  • empty or null values. Any difference? How to export them? What if the object itself is null?
  • how to handle the header of the CSV, where do you get the name of the properties?
  • what if the record type is an array or IEnumerable?
  • what will be the numeric and date formatting used for export?
  • does the candidate know what text encoding is? Which one will they use and why?

  How have the answers to these questions changed the design? Did the candidate redesign the work or held tight to the original idea and tried to fix everything as it comes?

  At this point you should know how the person being interviewed responds to new information, even scope creep and, maybe most importantly, to stress. But we're not done, are we?

Bring the pain

  Bring up the concept of unit testing. If you are lucky, the candidate already brought it up. Either way, now it is time to:

  • split the code into components: the reflection code, the export code, the file system code (if any).
  • abstract components into interfaces in order to mock them in unit tests
  • collect all the specifications gathered so far in order to cover all the cases
  • ask the candidate to write one unit test

Conclusion

  A seemingly simple question will take you and the interview candidate through:

  • finding out how the other person thinks
  • specification gathering
  • code design
  • implementation
  • technical knowledge in a multitude of directions
  • development process
  • separation of concerns, unit testing
  • human interaction in a variety of circumstances
  • determining how the candidate would fit in a team

Not bad for a one line question, right?

  I want to write this post to talk about the most common mistake I make as a software developer, even after almost 20 years of experience. And it's not code related. It's more human. But I would also like to hear what you think your biggest mistakes are that are not related to lack of experience. Don't be shy!

  My mistake: assumptions.

  I was assigned this bug recently and, wanting to do a fast job and impress people, I investigated the code, noticed a bug, fixed it, then immediately gave it in for review. I had reasons for doing that, because I was new and did not know the application well. The leads would tell me if they thought I did not find the problem. But, out of the goodness of my heart, you see, I've decided to test the fix as well. And I discovered that the feature was barely implemented. It was not a bug, it was a full fuck up.

  What happened here? I assumed a certain quality of the code and expected, without any reasonable evidence, to find a small typo or a logic bug that would be solved by writing a few lines of code. Instead, I had to reimplement the whole thing as a fix, I pissed off the lead devs because they had enough on their plate and made the entire team wonder what I was doing there. I mean, I haven't even tested the fix!

  Doing things fast means working on valid assumptions that allow you to cut corners. In a new environment, with a team you are not familiar with and a code base you don't understand, you do not have the luxury to make assumptions. Instead, do a good job first: investigate thoroughly, see what the reported problem is, find the actual problem (which may be different), come with an attack plan, implement it, then test that it had the desired result. Yes, it takes more time than to quickly compile the logic flow in your head and hope for the best, but in some places you don't get second chances at fixing things, teams are more formal, processes need to be followed. Optimism is also based on assumptions. Be a realist instead.

  In order to win a game you need to know its rules. That applies both to development process and to local politics, which sometimes are more important than the work. Once you are a good player, you can start experimenting. The title "senior developer" is not given in a vacuum, but is relevant (or not) depending on the environment. Yes, you have experience, but you don't have *this* experience yet. In my desire to be efficient and fast I didn't do anything right and I couldn't believe I have been that stupid.

  Now, how about you? What are your silly mistakes that you can't believe you are still making?

  I am subscribed to the StackOverflow newsletter and most of the times the "top" questions there are really simple things that gain attention from a lot of people. Today I got one question that I would have thought has an obvious answer, but it did not.

  The question was what does "asdf".replace(/.*/g,"x") return? 

  And the answer to the question "What does a regular expression replace of everything with x return?" is.... [Ba da bum!] "xx".

  The technical answer is there in the StackOverflow question, but I am gonna walk you through some steps to get to understand this the... dumb way.

  So, let's try variations on the same theme. What does "asdf".matchAll(/.*/g) return? Well, first of all, in Chrome, it returns a RegExpStringIterator, which is pretty cool, because it's already using the latest Javascript features and it is returning an iterator rather than an array. But we can just use Array.from on it to get an array of all matches: for "asdf" and for "".

  That's a pretty clear giveaway. Since the regular expression is a global one, it will get a match, then the next one until there is nothing left. First match is "asdf" as expected, the next one is "", which is the rest of the string and which also matches .* Why is it, then, that it doesn't go into a stack overflow (no pun intended) and keep turning up empty strings? Again, it's an algorithm described in an RFC and you need a doctorate in computer science to read it. Well, it's not that complicated, but I did promise a dumb explanation.

   And that is that after you get a match on an index, the index is incremented. First match is found at index 0, the next one at 4. There are no matches from index 5 on.

   Other variations on this theme are "asdf".matchAll(/.?/g), which will return "a","s","d","f","". You can't do "asdf".matchAll(/.*/) , you get a TypeError: undefineds called with a non-global RegExp argument error that really doesn't say much, but you can do "asdf".match(/.*/g) which returns just an array of strings, rather than more complex objects. You can also do

var reg = /.*/g;
console.log(reg.exec("asdf"),reg.exec("asdf"),reg.exec("asdf"),reg.exec("asdf"))

This more classic approach will return "asdf", "", "", "" and it would continue to return empty strings ad infinitum!

But how should one write a regular expression to get what you wanted to get, a replacement of everything with x? /.+/g would work, but it would not match an empty string. On the other hand, when was the last time you wanted to replace empty strings with anything?

  I am going to do this in Javascript, because it's easier to write and easier for you to test (just press F12 in this page and write it in the console), but it applies to any programming language. The issue arises when you want to execute a background job (a setTimeout, an async method that you do not wait, a Task.Run, anything that runs on another execution path than the current one) inside a for loop. You have the index variable (from 0 to 10, for example) and you want to use it as a parameter for the background job. The result is not as expected, as all the background jobs use the same value for some reason.

  Let's see a bit of code:

// just write in the console numbers from 0 to 9
// but delayed for a second
for (var i=0; i<10; i++)
{
  setTimeout(function() { console.log(i); },1000);
}

// the result: 10 values of 10 after a second!

But why? The reason is the "scope" of the i variable. In this case, classic (EcmaScript 5) code that uses var generates a value that exists everywhere in the current scope, which for ES5 is defined as the function this code is running from or the global scope if executed directly. If after this loop we write console.log(i) we get 10, because the loop has incremented i, got it to 10 - which is not less than 10, and exited the loop. The variable is still available. That explains why, a second later, all the functions executed in setTimeout will display 10: that is the current value of the same variable.

Now, we can solve this by introducing a local scope inside the for. In ES5 it looked really cumbersome:

for (var i=0; i<10; i++)
{
  (function() {
    var li = i;
    setTimeout(function() { console.log(li); },1000);
  })();
}

The result is the expected one, values from 0 to 9.

What happened here? We added an anonymous function and executed it. This generates a function scope. Inside it, we added a li variable (local i) and then set executing the timeout using that variable. For each value from 0 to 9, another scope is created with another li variable. If after this code we write console.log(li) we get an error because li is undefined in this scope. It is a bit confusing, but there are 10 li variables in 10 different scopes.

Now, EcmaScript 6 wanted to align Javascript with other common use modern languages so they introduced local scope for variables by defining them differently. We can now use let and const to define variables that are either going to get modified or remain constant. They also exist only in the scope of an execution block (between curly brackets).

We can write the same code from above like this:

for (let i=0; i<10; i++) {
  const li = i;
  setTimeout(()=>console.log(li),1000);
}

In fact, this is more complex than it has to be, but that's because another Javascript quirk. We can simplify this for the same result as:

for (let i=0; i<10; i++) {
  setTimeout(()=>console.log(i),1000);
}

Why? Because we "let" the index variable, so it only exists in the context of the loop execution block, but apparently it creates one version of the variable for each loop run. Strangely enough, though, it doesn't work if we define it as "const".

Just as an aside, this is way less confusing with for...of loops because you can declare the item as const. Don't use "var", though, or you get the same problem we started with!

const arr=[1,2,3,4,5];
for (const item of arr) setTimeout(()=>console.log(item),1000);

In other languages, like C#, variables exist in the scope of their execution block by default, but using a for loop will not generate multiple versions of the same variable, so you need to define a local variable inside the loop to avoid this issue. Here is an example in C#:

for (var i=0; i<10; i++)
{
    var li = i;
    Task.Run(() => Console.WriteLine(li));
}
Thread.Sleep(1000);

Note that in the case above we added a Thread.Sleep to make sure the app doesn't close while the tasks are running and that the values of the loop will not necessarily be written in order, but that's beside the point here. Also, var is the way variables are defined in C# when the type can be inferred by the compiler, it is not the same as the one in Javascript.

I hope you now have a better understanding of variable scope.

  If you are like me, you want to first establish a nice skeleton app that has everything just right before you start writing your actual code. However, as weird as it may sound, I couldn't find a way to use command line parameters with dependency injection, in the same simple way that one would use a configuration file with IOptions<T> for example. This post shows you how to use CommandLineParser, a nice library that handler everything regarding command line parsing, but in a dependency injection friendly way.

  In order to use command line arguments, we need to obtain them. For any .NET Core application or .NET Framework console application you get it from the parameters of the static Main method from Program. Alternately, you can use Environment.CommandLine, which is actually a string, not an array of strings. But all of these are kind of nudging you towards some ugly code that either has a dependency on the static Environment, either has code early in the application to handle command line arguments, or stores the arguments somehow. What we want is complete separation of modules in our application.

  How can we get the arguments by injection? By creating a new type that encapsulates the simple string array.

// encapsulates the arguments
public class CommandLineArguments
{
    public CommandLineArguments(string[] args)
    {
        this.Args = args;
    }

    public string[] Args { get; }
}

// adds the type to dependency injection
services.AddSingleton<CommandLineArguments>(new CommandLineArguments(args));
// the generic type declaration is superfluous, but the code is easy to read

  With this, we can access the command line arguments anywhere by injecting a CommandLineArguments object and accessing the Args property. But this still implies writing command line parsing code wherever we need that data. We could add some parsing logic in the CommandLineArguments class so that instead of the command line arguments array it would provide us with a strong typed value of the type we want. But then we would put business logic in a command line encapsulation class. Why would it know what type of options we need and why would we need only one type of options? 

  What we would like is something like

public SomeClass(IOptions<MyCommandLineOptions> clOptions) {...}

  Now, we could use this system by writing more complicated that adds a ConfigurationSource and then declaring that certain types are command line options. But I don't want that either for several reasons:

  • writing configuration providers is complex code and at some moment in time one has to ask how much are they willing to write in order to get some damn arguments from the command line
  • declaring the types at the beginning does provide some measure of centralized validation, but on the other hand it's declaring types that we need in business logic somewhere in service configuration, which personally I do not like

  What I propose is adding a new type of IOptions, one that is specific to command line arguments:

// declare the interface for generic command line options
public interface ICommandLineOptions<T> : IOptions<T>
    where T : class, new() { }

// add it to service configuration
services.AddSingleton(typeof(ICommandLineOptions<>), typeof(CommandLineOptions<>));

// put the parsing logic inside the implementation of the interface
public class CommandLineOptions<T> : ICommandLineOptions<T>
    where T : class, new()
{
    private T _value;
    private string[] _args;

    // get the arguments via injection
    public CommandLineOptions(CommandLineArguments arguments)
    {
        _args = arguments.Args;
    }

    public T Value
    {
        get
        {
            if (_value==null)
            {
                // set the value by parsing command line arguments
            }
            return _value;
        }
    }

}

  Now, in order to make it work, we will use CommandLineParser which functions in a very simple way:

  • declare a Parser
  • create a POCO class that has properties decorated with attributes that define what kind of command line parameter they are
  • parse the command line arguments string array into the type of class declared above
  • get the value or handle errors

  Also, to follow the now familiar Microsoft pattern, we will write an extension method to register both arguments and the mechanism for ICommandLineOptions. The end result is:

// extension class to add the system to services
public static class CommandLineExtensions
{
    public static IServiceCollection AddCommandLineOptions(this IServiceCollection services, string[] args)
    {
        return services
            .AddSingleton<CommandLineArguments>(new CommandLineArguments(args))
            .AddSingleton(typeof(ICommandLineOptions<>), typeof(CommandLineOptions<>));
    }
}

public class CommandLineArguments // defined above

public interface ICommandLineOptions<T> // defined above

// full class implementation for commmand line options
public class CommandLineOptions<T> : ICommandLineOptions<T>
    where T : class, new()
{
    private T _value;
    private string[] _args;

    public CommandLineOptions(CommandLineArguments arguments)
    {
        _args = arguments.Args;
    }

    public T Value
    {
        get
        {
            if (_value==null)
            {
                using (var writer = new StringWriter())
                {
                    var parser = new Parser(configuration =>
                    {
                        configuration.AutoHelp = true;
                        configuration.AutoVersion = false;
                        configuration.CaseSensitive = false;
                        configuration.IgnoreUnknownArguments = true;
                        configuration.HelpWriter = writer;
                    });
                    var result = parser.ParseArguments<T>(_args);
                    result.WithNotParsed(errors => HandleErrors(errors, writer));
                    result.WithParsed(value => _value = value);
                }
            }
            return _value;
        }
    }

    private static void HandleErrors(IEnumerable<Error> errors, TextWriter writer)
    {
        if (errors.Any(e => e.Tag != ErrorType.HelpRequestedError && e.Tag != ErrorType.VersionRequestedError))
        {
            string message = writer.ToString();
            throw new CommandLineParseException(message, errors, typeof(T));
        }
    }
}

// usage when configuring dependency injection
services.AddCommandLineOptions(args);

Enjoy!

Now there are some quirks in the implementation above. One of them is that the parser class generates the usage help by writing it to a TextWriter (default being Console.Error), but since we want this to be encapsulated, we declare our own StringWriter and then store the generated help if any errors. In the case above, I am storing the help text as the exception message, but it's the principle that matters.

Also, with this system one can ask for multiple types of command line options classes, depending on the module, without the need to declare said types at the configuration of dependency injection. The downside is that if you want validation of the command line options at the very beginning, you have to write extra code. In the way implemented above, the application will fail when first asking for a command line option that cannot be mapped on the command line arguments.

As a bonus, here is the way to define an option class that CommandLineParser will parse from the arguments:

// the way we want to use the app is
// FileUtil <command> [-loglevel loglevel] [-quiet] -output <outputFile> file1 file2 .. file10
public class FileUtilOptions
{
    // use Value for parameters with no name
    [Value(0, Required = true, HelpText = "You have to enter a command")]
    public string Command { get; set; }

    // use Option for named parameters
    [Option('l',"loglevel",Required = false, HelpText ="Log level can be None, Normal, Verbose")]
    public string LogLevel { get; set; }

    // use bool for named parameters with no value
    [Option('q', "quiet", Default = false, Required = false, HelpText = "Quiet mode produces no console output")]
    public bool Quiet { get; set; }

    // Required for required values
    [Option('o', "output", Required = true, HelpText = "Output file is required")]
    public string OutputFile { get; set; }

    // use Min/Max for enumerables
    [Value(1, Min = 1, Max = 10, HelpText = "At least one file name and at most 10")]
    public IEnumerable<string> Files { get; set; }
}

Note that the short style of a parameter needs to be used with a dash, the long one with two dashes:

  • -o outputFile.txt - correct (value outputFile.txt)
  • --output outputFile.txt - correct (value outputFile.txt)
  • -output outputFile.txt - incorrect (value utput and outputFile.txt is considered an unnamed argument)

Intro

  As I was working on LInQer I was hooked on the multiple optimizations that I was finding. Do you want to compute the average of an iterable? You would need the total count and the sum of the items, which you can get in a single function that you can reuse to get the sum or the count. But what if the iterable is an integer range between 1 and 10? Then you can compute the sum and you already know the count. Inspired by that work and by other concepts like interval types or Maybe/Nullable types, I've decided to write this post, which I do not know if it will lead to any usable code.

What is an iterable/enumerable?

  In Javascript they call it an Iterable, in .NET you have IEnumerable. They mean the same thing: sources of values. With new concepts like async/await you can use Observables as Enumerables as well, although they are theoretically diametrically opposing patterns. In both languages they are implemented as having a method that returns an iterator/enumerator, an object that can move to the next value, give you the next value and maybe reset itself. You can define any stream of values like that, having one or more values or, indeed, none. From now own I will discuss in terms of .NET nomenclature, but I see no reason why it wouldn't apply to any other language that implements this feature.

  For example an array is defined as an IEnumerable<T> in .NET. Its enumerator will return false if trying to move to the next value and the array is empty, or true if there is at least a value and the current value will return the first value in the array. Move next again and it will return true or false depending on whether there is a next value. But there is no need for the values to exist to have an Enumerable. One could write an object that would return all the positive integer numbers. It's length would be infinite and the values would only be generated when requested. There is no differentiation between an Enumerable and a generator in .NET, but there is in Javascript. For this reason whenever I will use the term generator, I will mean an object that generates values rather than produce them from a source of existing ones.

The NULL controversy

  A very popular InfoQ post describes the introduction of the NULL concept in programming languages a the billion dollar mistake. I am not so sure about that, but I can concede they make good points. The alternative to using a special value to describe the absence of a value is use an "option" object that either has Some value or it has None. You would check the existence of a value by calling a method to tell you if it has a value and you would get the value from the current value property. Doesn't it sound familiar? It's a more specific case of an Enumerator! Another popular solution to remove NULLs from code is to never return values from your methods, but arrays. An empty array would represent no value. An array is an Enumerable!

And that last idea opens up an interesting possibility: instead of one or none, you can have multiple values. What then? What would a multiplication mean? What about a decision block?

The LInQer experience

  If you know me, you are probably fed up with me plugging LInQer as the greatest thing since fire was invented. But that's because it is! And while implementing .NET LInQ as a Javascript library I've played with some very interesting concepts.

  For example, while implementing the Last operator on enumerables, I had two different implementations depending on whether one could know the length in advance and one could use indexed access to the values. An array of one billion values has no problem giving you the last item in it because of two things: you know where the array ends and you can access any item at any position without having to go through other values. You just take the value at index one billion minus one. If you would have a generator, though, the only way to get the last value would be to enumerate again and again and again and only when moving to the next value would fail you would have the last value as the last one. And of course, this would be bad if there are no bounds to the generator.

  But there is more. What about very common statistical values like the sum? This, of course, applies to numbers. The Enumerable need not produce numbers, so in other contexts it means nothing. Then there are concepts like statistical distribution. One can make some assumptions if they know the distribution of values. A constant yet infinite generator of numbers will always have the same average value. It would return the same value, regardless of index.

  I spent a lot of time doing sorting that only needs a part of the enumerable, or partial sorting. I've implemented a Quicksort algorithm that works faster than the default sort when there are enough values and that can ignore the parts of the array that I don't need. Also, there are specific algorithm to return the last or first N items. All of this depends on functions that determine the order of items. Randomness is also interesting, as it needs to take into consideration the change of probabilities as the list of items increases with each request. Sampling was fun, too!

  Then there were operators like Distinct or Group which needed to use functions to determine sameness.

  With all this work, I've never intended to make this more than what LInQ is in .NET: a way to dynamically filter and map and enumerate sequences of items without having to go through them all or to create intermediate but unnecessary arrays. What I am talking about now is taking things further and deeper.

Continuous intervals

  What if the Enumerable abstraction is not enough? For example one could define the interval of real numbers between 0 and 1. You can never enumerate the next value, but there are definite boundaries, a clear distribution of values, a very obvious average. What about series and limits? If a generator generates values that depend on previous values, like a geometric progression or a Fibonacci series, you can sometimes compute the minimum or maximum value of the items in it, or of their sums.  

Tools

  So we have more concepts in our bag now:

  • move next (function)
  • current value
  • item length (could be infinite or just unknown)
  • indexed access (or not)
  • boundaries (min, max, limits)
  • distribution (probabilities)
  • order
  • discreteness

  How could we use these?

Concrete cases

  There is one famous probabilities problem: what are the chances you will get a particular value by throwing a number of dice. And it is interesting because there is a marked difference between using one die or more. Using at least two dice and plotting the values you get after multiple throws you get what is called a Normal distribution, a Gauss curve, and that's because there are more combinations of values that sum up to 6 than there are for 2.

  How can we declare a value that belongs to an interval? One solution is to add all kinds of metadata or validations. But what if we just declare an iterable with one value that has a random value between 1 and 6? And what if we add it with another one? What would that mean?

  Here is a demo example. It's silly and it looks too much like the Calculator demos you see for unit testing and I really hate those, but I do want to just demo this. What else can we do with this idea? I will continue to think about it.

class Program
    {
        static void Main(string[] args)
        {
            var die1 = new RandomGenerator(1, 6);
            var die2 = new RandomGenerator(1, 6);
            // just get the value
            var value1 = die1.First() + die2.First();
            // compose the two dice using Linq, then get value
            var value2 = die1.Zip(die2).Select(z => z.First + z.Second).First();
            // compose the two dice using operator overload, then get value
            var value3 = (die1 + die2).First();
            var min = (die1 + die2).Min();
        }

        /// <summary>
        /// Implemented Min alone for demo purposes
        /// </summary>
        /// <typeparam name="T"></typeparam>
        public interface IGenerator<T> : IEnumerable<T>
        {
            int Min();
        }

        /// <summary>
        /// Generates integer values from minValue to maxValue inclusively
        /// </summary>
        public class RandomGenerator : IGenerator<int>
        {
            private readonly Random _rnd;
            private readonly int _minValue;
            private readonly int _maxValue;

            public RandomGenerator(int minValue, int maxValue)
            {
                _rnd = new Random();
                this._minValue = minValue;
                this._maxValue = maxValue;
            }

            public static IGenerator<int> operator +(RandomGenerator gen1, IGenerator<int> gen2)
            {
                return new AdditionGenerator(gen1, gen2);
            }

            public IEnumerator<int> GetEnumerator()
            {
                while (true)
                {
                    yield return _rnd.Next(_minValue, _maxValue + 1);
                }
            }

            IEnumerator IEnumerable.GetEnumerator()
            {
                return ((IEnumerable<int>)this).GetEnumerator();
            }

            public int Min()
            {
                return _minValue;
            }
        }
        
        /// <summary>
        /// Combines two generators through addition
        /// </summary>
        internal class AdditionGenerator : IGenerator<int>
        {
            private IGenerator<int> _gen1;
            private IGenerator<int> _gen2;

            public AdditionGenerator(Program.RandomGenerator gen1, Program.IGenerator<int> gen2)
            {
                this._gen1 = gen1;
                this._gen2 = gen2;
            }

            public IEnumerator<int> GetEnumerator()
            {
                var en1 = _gen1.GetEnumerator();
                var en2 = _gen2.GetEnumerator();
                while (true)
                {
                    var hasValue = en1.MoveNext();
                    if (hasValue != en2.MoveNext())
                    {
                        throw new InvalidOperationException("One generator stopped providing values before the other");
                    }
                    if (!hasValue)
                    {
                        yield break;
                    }
                    yield return en1.Current + en2.Current;
                }

            }

            IEnumerator IEnumerable.GetEnumerator()
            {
                return ((IEnumerable<int>)this).GetEnumerator();
            }

            public int Min()
            {
                return _gen1.Min() + _gen2.Min();
            }
        }
    }

Conclusion (so far)

I am going to think about this some more. It has a lot of potential as type abstraction, but to be honest, I deal very little in numerical values and math and statistics, so I don't see what I personally could do with this. I suspect, though, that other people might find it very useful or at least interesting. And yes, I am aware of mathematical concepts like interval arithmetic and I am sure there are a ton of existing libraries that already do something like that and much more, but I am looking at this more from the standpoint of computer science and quasi-primitive types than from a mathematical or numerical perspective. If you have any suggestions or ideas or requests, let me know!

  You can consider this an interview question, although to be fair if someone did ask me this for an interview I would say they are assholes. What is the difference between the pre-increment operator and the post-increment operator in C#?

  They look the same in C and C# and Javascript and Java and all the languages that share the curly bracket syntax with C, but in fact they are slightly different. Slight enough to make someone an asshole for asking the question as if it were relevant, but important enough for you to read about it. One of the most common interpretations of the syntax is that x++ is incrementing the value after the operation, while ++x is incrementing it before the operation. That is wrong.

  In fact, for C++ the return values are different between pre and post operators. I am not a C++ dev, so I give you this reference link: "Pre operators increment or decrement the value of the object and return a reference to the result. Post operators create a copy of the object, increment or decrement the value of the object and return the copy from before the increment or decrement." So one returns an object, the other returns a reference to an object. It is also possible that the assignment be done after the value was produced in C or C++. In C# the assignment must be done before any value is returned.

  In C#, to paraphrase Eric Lippert, "Both pre and post operators determine the value of the variable, what value will be assigned back to storage and assign the new value to storage. The postfix operator produces the original value, and the prefix operator produces the assigned value." So it's (kindda) like this piece of code:

int Increment(ref int x, bool post) {
  var originalX = x;
  var newX = x+1;
  x = newX;
  return post ? originalX : newX;
}

  So why the hell does it matter? I mean, it's a rather meaningless difference between the programming languages and the before/after mnemonic is making the code pretty clear, doesn't it? OK. Let's try some code and let me see how fast you come up with the answer. Remember, this is supposed to be simple, so if you are thinking too much about it, it doesn't matter you get the correct answer. Ready?

  1. Any difference between x++ and ++x if the resulting value is not used?
  2. var a=1; var b=++a; What's the value of b?
  3. var a=1; var b=a++; var c=++a; What's the value of c?
  4. var i = 0; for (i=0; i<5; ++i) Console.Write(i+" "); Console.WriteLine(i); What is printed at the console?
  5. var i = 0; for (i=0; i<5; i++) Console.Write(i+" "); Console.WriteLine(i); What is printed at the console?
  6. var a=1; a=a++; What's the value of a?

And all of this was about the increment operator as normally used for integer values. There is a big part about operator overloading in there, but I believe less relevant in the context of differences between pre and post increment/decrement operators.

There is one important part to discuss, though, and that is best code practices. When to use post and when to use pre. And they are really easy: separate statements from expressions! Statements execute code with side effects, they should return nothing. Expressions return values without side effects. If you never use the value of an increment or decrement and instead use it as a statement with side-effects, there is no difference between ++a and a++. In fact one doesn't need the preincrement/predecrement operators at all! In this context, the answers for the questions above is 1. No 2,3,6: You are using it wrong! 4,5: the same thing, since without getting the value we have scenario 1.

Just for reference, though, here are the answers:

  1. No
  2. 2
  3. 3 (b is 1)
  4. 0 1 2 3 4 5
  5. 0 1 2 3 4 5
  6. 1

Hope that makes you think.

 Intro

  When I was a kid, computers didn't have multithreading, multitasking or even multiple processes. You executed a program and it was the only program that was running. Therefore the way to do, let's say, user key input was to check again and again if there is a key in a buffer. To give you a clearer view on how bonkers that was, if you try something similar in Javascript the page dies. Why? Because the processing power to look for a value in an array is minuscule and you will basically have a loop that executes hundreds of thousand or even millions of times a second. The CPU will try to accommodate that and run at full power. You will have a do nothing loop that will take the entire capacity of the CPU for the current process. The browser would have problems handling legitimate page events, like you trying to close it! Ridiculous!

Bad solution

Here is what this would look like:

class QBasic {

    constructor() {
        this._keyBuffer=[];
        // add a global handler on key press and place events in a buffer
        window.addEventListener('keypress', function (e) {
            this._keyBuffer.push(e);
        }.bind(this));
    }

    INKEY() {
        // remove the first key in the buffer and return it
        const ev = this._keyBuffer.shift();
        // return either the key or an empty string
        if (ev) {
            return ev.key;
        } else {
            return '';
        }
    }
}

// this code will kill your CPU and freeze your page
const qb = new QBasic();
while (qb.INKEY()=='') {
 // do absolutely nothing
}

How then, should we port the original QBasic code into Javascript?

WHILE INKEY$ = ""

    ' DO ABSOLUTELY NOTHING

WEND

Best solution (not accepted)

Of course, the best solution is to redesign the code and rewrite everything. After all, this is thirty year old code. But let's imagine that, in the best practices of porting something, you want to find the first principles of translating QBasic into Javascript, then automate it. Or that, even if you do it manually, you want to preserve the code as much as possible before you start refactoring it. I do want to write a post about the steps of refactoring legacy code (and as you can see, sometimes I actually mean legacy, as in "bestowed upon by our forefathers"), but I wanted to write something tangible first. Enough theory!

Interpretative solution (not accepted, yet)

Another solution is to reinterpret the function into a waiting function, one that does nothing until a key is pressed. That would be easier to solve, but again, I want to translate the code as faithfully as possible, so this is a no-no. However, I will discuss how to implement this at the end of this post.

Working solution (slightly less bad solution)

Final solution: do the same thing, but add a delay, so that the loop doesn't use the entire pool of CPU instructions. Something akin to Thread.Sleep in C#, maybe. But, oops! in Javascript there is no function that would freeze execution for a period of time.

The only thing related to delays in Javascript is setTimeout, a function that indeed waits for the specified interval of time, but then executes the function that was passed as a parameter. It does not pause execution. Whatever you write after setTimeout will execute immediately. Enter async/await, new in Javascript ES8 (or EcmaScript 2017), and we can use the delay function as we did when exploring QBasic PLAY:

function delay(duration) {
    return new Promise(resolve => setTimeout(resolve, duration));
}

Now we can wait inside the code with await delay(milliseconds);. However, this means turning the functions that use it into async functions. As far as I am concerned, the pollution of the entire function tree with async keywords is really annoying, but it's the future, folks!

Isn't this amazing? In order to port to Javascript code that was written in 1990, you need features that were added to the language only in 2017! If you wanted to do this in Javascript ES5 you couldn't do it! The concept of software development has changed so much that it would have been impossible to port even the simplest piece of code from something like QBasic to Javascript.

Anyway, now the code looks like this:

function delay(duration) {
    return new Promise(resolve => setTimeout(resolve, duration));
}

class QBasic {

    constructor() {
        this._keyBuffer=[];
        // add a handler on every key press and place events in a buffer
        window.addEventListener('keypress', function (e) {
            this._keyBuffer.push(e);
        }.bind(this));
    }

    async INKEY() {
        // remove the first key in the buffer and return it
        const ev = this._keyBuffer.shift();
        // return either the key or an empty string
        if (ev) {
            return ev.key;
        } else {
            await delay(100);
            return '';
        }
    }
}

const qb = new QBasic();
while (qb.INKEY()=='') {
 // do absolutely nothing
}

Now, this will work by delaying for 100 milliseconds when there is nothing in the buffer. It's clearly not ideal. If one wanted to fix a problem with a loop running too fast, then the delay function should have at least been added to the loop, not the INKEY function. Using it like this you will get some inexplicable delays in code that would want to use fast key inputs. It's, however, the only way we can implement an INKEY function that will behave as close to the original as possible, which is hiring a 90 year old guy to go to a letter box and check if there is any character in the mail and then come back and bring it to you. True story, it's the original implementation of the function!

Interpretative solution (implementation)

It would have been much simpler to implement the function in a blocking manner. In other words, when called, INKEY would wait for a key to be pressed, then exit and return that key when the user presses it. We again would have to use Promises:

class QBasic {

    constructor() {
        this._keyHandler = null;
        // instead of using a buffer for keys, keep a reference
        // to a resolve function and execute it if it exists
        window.addEventListener('keypress', function (e) {
            if (this._keyHandler) {
                const handler = this._keyHandler;
                this._keyHandler = null;
                handler(e.key);
            }
        }.bind(this));
    }

    INKEY() {
        const self = this;
        return new Promise(resolve => self._keyHandler = resolve);
    }
}


const qb = new QBasic();
while ((await qb.INKEY())=='') { // or just await qb.INKEY(); instead of the loop
 // do absolutely nothing
}

Amazing again, isn't it? The loops (pun not intended) through which one has to go in order to force a procedural mindset on an event based programming language.

Disclaimer

Just to make sure, I do not recommend this style of software development; this is only related to porting old school code and is more or less designed to show you how software development has changed in time, from a period before most of you were even born.

Intro

  This is part of a series that I plan to build on as time goes on: technical interview questions, dissected and laid bare for both interviewers and interviewees. You can also check out the previous one: Interview question: all items in table A but not in B.

  This question is a little bit more complex and abstract at the same time. The post is written more for interviewers this time, because as candidates go, you need to read the links in it if you didn't know the concepts in it. This also is not a question with a single correct answer. It comes after asking about Dependency Injection as a whole and the candidate answering correctly.

  I expect senior developers to be able to go through this successfully, it is not a test for junior developers, although depending on their previous experience juniors might be able to go through it and seniors be force to reason through it.

The test

Bonus introduction question: why use DI at all? Expected answers would be separation of concerns and testability. 

  The question has two steps.

Step 1: given the following code in a legacy application, improve it to use Dependency Injection:

public SomeClass {
  public List<Item> GetItems(int days, string filter) {
    var service = new ItemService();
    return service.GetItems()
      .Where(i => i.Time >= DateTime.Now.AddDays(-days));
  }
}

Bonus questions:

  • has the candidate worked with LINQ before?
  • what does the code do?

Now, this question is about programming knowledge as it is for attention. There are three irregularities that can attract that attention:

  • the most obvious: the service is being instantiated by calling the constructor
    • the interviewer expects at the very least for the candidate to notice it and suggest moving the instantiation of the service in the constructor of the SomeClass class and inject it instead of using new
    • there is the possibility of passing the service as a parameter, as well, but suggest that the signature of the method should remain the same to get around it. Anyway, one can discuss the idea of moving all dependencies to the constructor and/or the calling methods and get insight in the way the candidate is thinking.
  • the unexplained string filter in the signature of the method
    • the interviewer can either tell the candidate that it will become relevant later, because it will, or that this is a method that implements an interface, to which a more snarky candidate might reply that SomeClass implements nothing (bonus for attention)
  • the use of DateTime.Now
    • it is a static property that gives a different output every time so it should be taken into account for Dependency Injection or at least for unit testing

By now you have filtered out the majority of failing candidates and you are left with someone who used or at least understands DI, can read and understand code, has used or at least understood basic LINQ and you have also gauged their level of attention to detail.

If the candidate only talked about the service and they decided to create an interface for ItemService and then add it as a parameter for the constructor of SomeClass, ask them to write a unit test for the method, explain to them that testability is one of the goals of DI if you didn't cover this already

  • bonus: see if they do unit testing or at least understand the concept
  • if they do attempt to write the unit test, ask them what would happen if you would run the test in different days

The expected result of this part is that the candidate understands the need of abstracting DateTime.Now. It is interesting to note how they intend to abstract it, since they do not have access to the code and it is a static method/property to abstract.

Whether the candidate figured it out by themselves or it was explained to them, the expected answer is that DateTime.Now is abstracted by creating an IDateTimeService interface that is implemented as a wrapper over DateTime.

At this point the code should look like this:

public SomeClass {
  private IItemService _itemService;
  private IDateTimeService _dateTimeService;

  public SomeClass(IItemService itemService, IDateTimeService dateTimeService) {
    _itemService = itemService;
    _dateTimeService = dateTimeService;
  }

  public List<Item> GetItems(int days, string filter) {
    return _itemService.GetItems()
      .Where(i => i.Time >= _dateTimeService.Now.AddDays(-days));
  }
}

Also, the candidate should be asked to write a unit test, just to see they know how, for bonus points. Note if the candidate understands isolation for unit testing or does something that would work but be silly like generate the test data based on current date or duplicate the code logic in the test instead of working with static data.

Step 2: tell the candidate that the legacy code they need to fix looks a bit different:

public SomeClass {
  public List<Item> GetItems(int days, string filter) {
    var service = new ItemService(filter);
    return service.GetItems()
      .Where(i => i.Time >= DateTime.Now.AddDays(-days));
  }
}

The ItemService now receives the filter as the parameter. Ask them what to do in this case.

The expected answer is a factory injected instead of the service, which will then be used to instantiate an IItemService with a parameter. Bonus discussion about software patterns can be inserted here.

There are other valid answers here, like using the DI container itself as a factory for the service, which might provoke interesting discussions in itself, like weighing constructor injection versus service provider in dependency injection and whether hybrid solutions might be better.

Bonus question: what if you cannot control the code of ItemService in step 1 and it does not implement an interface or a base class?

  • warning, this might give a hint for the second part of the interview, so use it at the end 
  • correct answer 1: use the class as the type of the parameter and let the dependency container decide how to instantiate it
  • correct answer 2: use a wrapper over the class that implements the interface and proxies to the instance methods.

Conclusion

For me this test told me a lot more about the candidate than just their dependency injection knowledge. We got to talking, I became aware of how their minds worked and I was both pleasantly surprised when they came with alternate solutions that kind of worked and a bit irked that they went that far and didn't see the superior option. Most of the time this made me think about the differences between what I would answer and what they did and this resulted in interesting discussions that enriched not only their experience, but also mine.

Dependency injection, separation of concerns and unit testing are important concepts for any modern developer. I hope this helps devs evolve and interviewers find the best candidates... at least until all of them get to read my blog.

Summary

Once you finished with the foundation, it doesn't matter who you call to architect your house or fix problems you might have. Businesses and software are exactly like that. Think hard about your foundation, it will save you a lot of effort later on. I've been working in a lot of different places and was surprised to see they didn't know there are other ways of doing things. I distill the foundational principles one needs for a good software solution and maybe not just software:

  • Separation of concerns - processes, components and people should be able to function in isolation. If you can test they work when everything else is shut down, you're good. People should only do what they are good at. Components should do only one thing.
  • Cleanliness - keep your code readable rather than efficient, your process flow intuitive, roles and responsibilities clear. Favor convention over documentation, document anything else.
  • Knowledge sharing - Allow knowledge to be free and alive in your organization by promoting knowledge sharing, collaborative documentation, searchability.

Intro

  I am not the greatest of all developers or architects, but I am good. I know how things should be and what they should do in order to reach a goal. When people ask me about software, my greatest gaps are around specific software tools or some algorithm, not the general craft. That is because of several reasons: I enjoy my work, I've been really enthusiastic in my youth and sponged everything I could in order to become better and I've worked in many different types of organizations so I know multiple ways in which people have tried to do this. As I grow older, the last one may be my most valuable skill, but I am yet to find the employer to realize this.

  You see, what I've learned from my career so far is that most businesses live in a bubble. Used to not only learn software development as I am working on some task, but also network with other people in the craft from all across the business, I kind of expected every other developer to be like that. Or at least the senior devs, the dev leads and architects, maybe some managers. But no, most of the time, people are stuck in their little position and never stray from it. They may invoke life work balance, or they are just burned out, or they just don't care enough, but more often, they haven't even realized what they are missing. And that's the bubble. A bubble is not a prison, is just a small area in which people stay voluntarily and never get out of.

  This is why gaming development is so different from business app development. That is why development in an administrative business with a small software department is so different from development in a software company. It is why development in small shops is so different than in large software companies. Sometimes people, really smart people, have worked for a long time in only one of these ecosystems and they only know that one. They can hardly conceive of different ways to do things.

  So this is why I am writing this post, to talk about the foundations of things, that part that separates one from the other, forever, no matter what you do afterwards. And this applies to business, people organization, but especially well to large software projects. You see, if you start your solution badly, it will be bad until you rewrite it. Just like a building with a weak foundation. It doesn't matter you bring the best workers and architects afterwards, they will only build a wonderful house that will fall down when the foundation fails. You want to make a good thing, first plan it through and build the greatest foundation you can think of and afford. It's much easier to change the roof than the foundation.

  And you wouldn't believe how many times I've been put in the situation of having to fix the unfixable. "Hey, you're smart, right? We started this thing a million years ago, we thought we would save some money, so we got a bunch of junior developers to do it, and it worked! But then it didn't anymore. Fix it!" And I have to explain it to them: you can't scale duct tape. You can go only so much with a thing held together by paper clips, chewing gum and the occasional hero employee with white hair and hunched back and in his twenties.

  Now of course, to an entitled senior engineer like me any software evokes the instinct to rewrite it in their own image. "Also, get some juniors to carve my face into that hill over there!". Sometimes it's just a matter of adapting to the environment, work with what you have. But sometimes you just have to admit things are beyond salvation. Going forward is just a recipe for disaster later on. It's the law of diminishing returns when the original returns were small to begin with. And you wouldn't believe how many people agree with that sentiment, then declare there is nothing that can be done. "They won't give us the budget!" is often muttered. Sometimes it's "We only need this for a few years. After that we start from scratch" and in a few years some "business person" makes a completely uninformed cost and gain analysis and decides building up from existing code is cheaper than starting over. But don't worry, they will suuuurely start from scratch next time.

  Sometimes the task of rewriting something is completely daunting. It's not just the size of it, or the feeling that you've achieved nothing if you have to start over to do the same thing. It's the dread that if you make the same thing and it takes less effort and less money and it works better then you must be inferior. And it's true! You sucked! Own it and do better next time. It's not the same thing, it's version 2.0. You now have something that you couldn't have dreamed of when building version 1.0: an overview. You know what you need, not what you think you will need. Your existing project is basically the D&D campaign you've played so many times that it has become a vast landscape, rich with characters and story. You've mapped it all down.

  This post is an overview. Use it! To be honest, reaching this point is inevitable, there will always be a moment when a version 2.0 makes more sense than continuing with what you have. But you can change how terrible your software is when you get to it. And for this you need the right foundation. And I can teach you to do that. It's not even hard.

Separation of Concerns

  Most important thing: separation of concerns. Components should not be aware of each other. Compare a Lego construction to a brick and mortar one. One you can disassemble and reassemble, adding to it whatever you need, the other you need to tear down and rebuild from zero. Your foundation needs to allow and even enable this. Define clear boundaries that completely separate the flow into independent parts. For example a job description is an interface. It tells the business that if the person occupying a job leaves, another can come and take their place. The place is clearly defined as a boundary that separates a human being from their role in the organization.

  Software components, too, need to be abstracted as interfaces in order to be able to swap them around. And I don't mean the exact concept of interface from some programming languages. I mean that as loosely as one can. A web service is an interface, since it abstracts business logic from user interface. A view model is an interface, as it abstracts the user interface logic from its appearance. A website is an interface, as it performs a different task than another that is completely separated. If you can rewrite an authorization component in isolation and then just replace the one you have and the application continues to work as before, that means you have done well.

  Separation of concerns should also apply to your work process and the people in it. A software developer should not have to do much outside developing software. A manager should just manage. People should only be in meetings that bring value and should only be in those that actually concern them. If the process becomes too cumbersome, split it up into smaller pieces, hire people to handle each of them. Free the time of your employees to do the job they are best suited for. 

  One important value you gain from isolating components is testing. In fact, you can use testing as a force towards separation of concerns. If you can test a part of your application in isolation (so all other parts do not need to be working for it), then you have successfully separated concerns. Consider a fictional flow: you get on the bus, you get to the market, you find a vegetable stand, you buy a kilo of tomatoes, you get back to the bus, you come home. Now, if you can successfully test your ability to get on a bus, any bus, to get anywhere the bus is going, in order to test that you can buy tomatoes from the market you just test you can find the stand and buy the tomatoes. Then, if you can test that you can buy anything at any type of stand, you only need to test your ability to find a stand in a market.

  It seems obvious, right? It feels that way to me. Even now, writing this post, I am thinking I sound like an idiot trying to seem smart, but I've seen droves of developers who don't even consider this. Businesses who are not even aware of this as a possibility. "We have testing teams to make sure the application is working end to end, we don't need unit testing" or "We have end to end automated testing. For each new feature we write new tests". When you hear this, fight it. Their tests, even if written correctly and maintained perfectly, will take as long as one needs to get on a bus and go to the market. And then the other test will take as long as one need to get on a train and get to the airport. And so on. End to end testing should exist and if you can automate it, great, but it should be sparse, it should function like an occasional audit, not something that supports your confidence in the solution working correctly.

  So go for testable, not for tests. Tests often get a bad wrap because someone like me comes and teaches a company to write tests, then they leave and the people in the company either skip testing occasionally or they change bits of the application and don't bother to update the tests. This leads to my next point: clean code.

Cleanliness

  Cleanliness applies to everything, again. The flow of your solution (note that I am being as general as possible) needs to be as clear as possible, at every level. In software this usually translates in readable code and builds up from that. Someone looking at the code should be able to instantly and easily understand what it does. Some junior developers want to write their code as efficient as possible. They just read somewhere that this method is faster than the other method and want to put that in code. But it boils down to a cost analysis: if they shave one second off a process you run ten times a day, they save one hour per year; if another developer has to spend more than one hour to understand what the code does, the gain means nothing.

  Code should be readable before being fast. Comments in code should document decisions, not explain what is going on. Comments should display information from another level than the code's. Component names, object names, method names, variable names should be self explanatory. Configuration structures, property names, property values, they should be intuitive and discoverable.

  And there is another aspect to cleanliness. Most development environments have some automated checks for your code. You can add more and even make your own. This results in lists of errors, warnings and notifications. On a flow level, this might translate to people complaining about various things, some in key positions, some not. Unit tests, once you have them, might be passing or failing. It is important to clean that shit up! Do not ignore warnings or even notifications. You think a warning is wrong, find a way to make it go away, not by ignoring it, but by replacing the complaining component, marking it specifically in the code as not a valid warning and document why, run all the tests and make sure they are green or remove the tests that you think are not important (this should not happen usually). The reason is simple: in a sea of ignored warnings you will not see the one that matters.

  To be perfectly clear: by clean code I don't mean code that follows design patterns, I don't mean documentation comments on every property and method, I don't mean color coded sections (although that's nice). What I mean is code clean enough to read without cringing or having to look in ten other places to figure out what it does. If your hotdog falls on that code you should be comfortable enough to pick it up and continue eating it.

  Cleanliness should and must be applied to your work process. If the daily meeting is dirty (many people talking about unrelated things) then everybody is wasting time. If the process of finishing a task is not clear, you will have headless chickens instead of professionals trying to complete it. If you have to ask around where to log your hours or who is responsible for a specific job that you need done in order to continue, you need to clean that process. Remove all superfluous things, optimize remaining ones. Remember separation of concerns.

  Cleanliness extends to your project folder structure, your solution structure, your organizational structure. It all has to be intuitive. If you declare a principle, it should inform every query and decision, with no exception. "All software development people are at the fifth floor! Ugh... all except Joe". What if you need Joe? What if you don't know that you need Joe, but you still need him? Favor convention over configuration/documentation, document everything else. And that leads me to the final point: knowledge sharing.

Knowledge Sharing

  To me, knowledge sharing was always natural. In small companies there was always "that guy" who would know everything and couldn't work at all because people came to ask him things. In medium companies there was always some sort of documentation of decisions and project details. In large companies there were platforms like Confluence where people would share structured information, like the complete description of tasks: what they are about, how decisions were made, who is responsible for what, how they were split into specific technical tasks, what problems arose, what the solutions were, etc. And there were always your peers that you could connect to and casually talk about your day.

  Imagine my surprise to find myself working in places where you don't know what anyone else is doing, where you don't know what something is and what it is supposed to do, there are no guidelines outside random and out of date Powerpoint files, where I am alone with no team, brought in for problems that need strong decisions in order to fix but no one is willing to make them, and already I have no idea who should even attempt to. I solve a common problem, I want to share the solution, there is no place to do that. People are not even in the same building as me. Emails are come and go and no one has time to read them.

  Knowledge should live freely in your company. You should be able to search for anything and find it, be able to understand it, contribute to it, add more stuff. It should be more natural for the people in your company to write a blog post than go for coffee and complain. It should be easier to find and consume information from people that left the company than to get it from colleagues at the desk next to you. And maybe this cannot be generalized to all departments, but it is fucking important: people in the office should never need to open Microsoft Office (or any similar product suite). I can't stress that enough.

  You should not need printed documents, so no need for Word. Excel files are great for simple data tasks, but they are not specific. If you need something done repeatedly and you use Excel sheet, it is probably better to build a tool for it. Don't reinvent the wheel now, but use the best tool for the job. And there are better and more modern tools than Powerpoint files, but I will allow the use of them because, in the context of knowledge sharing, everyone should feel free and confident enough to make presentation for the team. My tenet still stands, though: the Powerpoint file would be used in a presentation. Hardly anyone else should need to open it. I mean, there would be a video of the presentation available, right?

Vision

  Imagine a park. It is sunny, birds are singing, there are people walking on hardened dirt walkways, cyclers biking on their asphalted bike lanes, benches everywhere, with a small notepad attached to them that people can just pick up and read or write their own notes. Places in the park are clearly indicated with helpful arrows: children playground, hotdog stand, toilet, football field, bar, ice ring. Everything is clean, everybody is doing what they do best, all is good. You feel hungry, you see the arrow pointing towards the hotdog stand, you walk there calmly and ask for one. The boy there give you a bun and a wurst. He is new, but he has a colleague that knows exactly how much mustard and ketchup to put on the hotdog. He even asks you if you want curry on it. 

  Imagine a park. It is sunny, birds are singing. Some walkways start of as asphalt, then continue as dirt. Some stop suddenly or end in a ditch. There is a place that serves hotdogs next to a toilet. You have to ask around to find out where to find it. You get lost several times, as some people don't know either, but they still come with an opinion, or they are just misinformed. You get tired, but you can't sit on a bench, they are all taken and there are so few of them. You have to look both ways several times before you walk to the stand, because of cyclers. You stand in a line, then order a hotdog. The boy there gives you a bun with a wurst in it. You ask for mustard, but the boy is new and it takes him a while to find it after looking for some paper that tells him where it is. You have to dodge a football that was coming at your head. Someone flushes the toilet.

Intro

  This post will take you on an adventure through time and sound. It will touch the following software development concepts:

  • await/async in Javascript
  • named groups in regular expressions in Javascript
  • the AudioContext API in Javascript
  • musical note theory
  • Gorillas!

  In times immemorial, computers were running something called the DOS operating system and almost the entire interface was text based. There was a way to draw things on the screen, by setting the values of pixels directly in the video memory. The sound was something generated on a "PC speaker" which was a little more than a small speaker connected to a power port and which you had to make work by handling "interrupts". And yet, since this is when I had my childhood, I remember so many weird little games and programs from that time with a lot of nostalgic glee.

  One of these games was Gorillas, where two angry gorillas would attempt to murder each other by throwing explosive bananas. The player would have to enter the angle and speed and also take into account a wind speed that was displayed as an arrow on the bottom of the screen. That's all. The sounds were ridiculous, the graphics really abstract and yet it was fun. So, as I was remembering the game, I thought: what would it take to make that game available in a modern setting? I mean, the programming languages, the way people thought about development, the hardware platform, everything has changed.

  In this post I will detail the PLAY command from the ancient programming language QBASIC. This command was being used to generate sound by instructing the computer to play musical notes on the PC speaker. Here is an example of usage:

PLAY "MBT160O1L8CDEDCDL4ECC"

  This would play the short song at the beginning of the Gorillas game. The string tells the computer to play the sound in the background, at a tempo of 160 in the first octave, with notes of an eighth of a measure: CDEDCD then end with quarter measure notes: ECC. I want to replicate this with Javascript, one because it's simpler to prototype and second because I can make the result work in this very post.

Sound and Music

  But first, let's see how musical notes are being generated in Javascript, using the audio API. First you have to create an AudioContext instance, with which you create an Oscillator. On the oscillator you set the frequency and then... after a while you stop the sound. The reason why the API seems so simplistic is because it works by creating an audio graph of nodes that connect to each other and build on each other. There are multiple ways in which to generate sound, including filling a buffer with data and playing that, but I am not going to go that way.

  Therefore, in order to PLAY in Javascript I need to translate concepts like tempo, octaves, notes and measures into values like duration and frequency. That's why we need a little bit of musical theory.

  In music, sounds are split into domains called octaves, each holding seven notes that, depending on your country, are either Do, Re, Mi, Fa, So, La, Si or A, B,C, D, E, F and G or something else. Then you have half notes, so called sharp or flat notes: A# is half a note above A and A♭ is a half note below A. A# is the same as B♭. For reasons that I don't want to even know, the octaves start with C. Also the notes themselves are not equally spaced. The octaves are not of the same size, in terms of frequency. Octave 0 starts at 16.35Hz and ends at 30.87, octave 1 ranges between 32.70 and 61.74. In fact, each octave spreads on twice as much frequency space as the one before. Each note has twice the frequency of the same note on the lower octave.

  In a more numerical way, octaves are split into 12: C, C#, D, E♭, E, F, F#, G, G#, A, B♭, B. Note (heh heh) that there are no half notes between B and C and E and F. The frequency of one of these notes is 21/12 times the one before. Therefore one can compute the frequency of a note as:

Frequency = Key note * 2n/12, where the key note is a note that you use as a base and n is the note-distance between the key note and the note you want to play.

  The default key note is A4, or note A from octave 4, at 440Hz. That means B♭ has a frequency of 440*1.059463 = 466.2.

  Having computed the frequency, we now need the duration. The input parameters for this are: tempo, note length, mode and the occasional "dot":

  • tempo is the number of quarter measures in a minute
    • this means if the tempo is 120, a measure is 60000 milliseconds divided by 120, then divided by 4, so 125 milliseconds
  • note length - the length of a note relative to a measure
    • these are usually fractions of a measure: 1, 1/2, 1/4, 1/8, 1/16, etc
  • mode - this determines a general speed of playing the melody
    • as defined by the PLAY command, you have:
      • normal: a measure is 7/8 of a default measure
      • legato: a measure is a measure
      • staccato: a measure is 3/4 of a default measure
  • dotted note - this means a specific note will be played for 3/2 of the defined duration for that note

  This gives us the formula:

Duration = note length * mode * 60000 / 4 / tempo * dotDuration

Code

  With this knowledge, we can start writing code that will interpret musical values and play a sound. Now, the code will be self explanatory, hopefully. The only thing I want to discuss outside of the audio related topic is the use of async/await in Javascript, which I will do below the code. So here it is:

class QBasicSound {

    constructor() {
        this.octave = 4;
        this.noteLength = 4;
        this.tempo = 120;
        this.mode = 7 / 8;
        this.foreground = true;
        this.type = 'square';
    }

    setType(type) {
        this.type = type;
    }

    async playSound(frequency, duration) {
        if (!this._audioContext) {
            this._audioContext = new AudioContext();
        }
        // a 0 frequency means a pause
        if (frequency == 0) {
            await delay(duration);
        } else {
            const o = this._audioContext.createOscillator();
            const g = this._audioContext.createGain();
            o.connect(g);
            g.connect(this._audioContext.destination);
            o.frequency.value = frequency;
            o.type = this.type;
            o.start();
            await delay(duration);
            // slowly decrease the volume of the note instead of just stopping so that it doesn't click in an annoying way
            g.gain.exponentialRampToValueAtTime(0.00001, this._audioContext.currentTime + 0.1);
        }
    }

    getNoteValue(octave, note) {
        const octaveNotes = 'C D EF G A B';
        const index = octaveNotes.indexOf(note.toUpperCase());
        if (index < 0) {
            throw new Error(note + ' is not a valid note');
        }
        return octave * 12 + index;
    }

    async playNote(octave, note, duration) {
        const A4 = 440;
        const noteValue = this.getNoteValue(octave, note);
        const freq = A4 * Math.pow(2, (noteValue - 48) / 12);
        await this.playSound(freq, duration);
    }

    async play(commandString) {
        const reg = /(?<octave>O\d+)|(?<octaveUp>>)|(?<octaveDown><)|(?<note>[A-G][#+-]?\d*\.?)|(?<noteN>N\d+\.?)|(?<length>L\d+)|(?<legato>ML)|(?<normal>MN)|(?<staccato>MS)|(?<pause>P\d+\.?)|(?<tempo>T\d+)|(?<foreground>MF)|(?<background>MB)/gi;
        let match = reg.exec(commandString);
        let promise = Promise.resolve();
        while (match) {
            let noteValue = null;
            let longerNote = false;
            let temporaryLength = 0;
            if (match.groups.octave) {
                this.octave = parseInt(match[0].substr(1));
            }
            if (match.groups.octaveUp) {
                this.octave++;
            }
            if (match.groups.octaveDown) {
                this.octave--;
            }
            if (match.groups.note) {
                const noteMatch = /(?<note>[A-G])(?<suffix>[#+-]?)(?<shorthand>\d*)(?<longerNote>\.?)/i.exec(match[0]);
                if (noteMatch.groups.longerNote) {
                    longerNote = true;
                }
                if (noteMatch.groups.shorthand) {
                    temporaryLength = parseInt(noteMatch.groups.shorthand);
                }
                noteValue = this.getNoteValue(this.octave, noteMatch.groups.note);
                switch (noteMatch.groups.suffix) {
                    case '#':
                    case '+':
                        noteValue++;
                        break;
                    case '-':
                        noteValue--;
                        break;
                }
            }
            if (match.groups.noteN) {
                const noteNMatch = /N(?<noteValue>\d+)(?<longerNote>\.?)/i.exec(match[0]);
                if (noteNMatch.groups.longerNote) {
                    longerNote = true;
                }
                noteValue = parseInt(noteNMatch.groups.noteValue);
            }
            if (match.groups.length) {
                this.noteLength = parseInt(match[0].substr(1));
            }
            if (match.groups.legato) {
                this.mode = 1;
            }
            if (match.groups.normal) {
                this.mode = 7 / 8;
            }
            if (match.groups.staccato) {
                this.mode = 3 / 4;
            }
            if (match.groups.pause) {
                const pauseMatch = /P(?<length>\d+)(?<longerNote>\.?)/i.exec(match[0]);
                if (pauseMatch.groups.longerNote) {
                    longerNote = true;
                }
                noteValue = 0;
                temporaryLength = parseInt(pauseMatch.groups.length);
            }
            if (match.groups.tempo) {
                this.tempo = parseInt(match[0].substr(1));
            }
            if (match.groups.foreground) {
                this.foreground = true;
            }
            if (match.groups.background) {
                this.foreground = false;
            }

            if (noteValue !== null) {
                const noteDuration = this.mode * (60000 * 4 / this.tempo) * (longerNote ? 1 : 3 / 2);
                const duration = temporaryLength
                    ? noteDuration / temporaryLength
                    : noteDuration / this.noteLength;
                const A4 = 440;
                const freq = noteValue == 0
                    ? 0
                    : A4 * Math.pow(2, (noteValue - 48) / 12);
                const playPromise = () => this.playSound(freq, duration);
                promise = promise.then(playPromise)
            }
            match = reg.exec(commandString);
        }
        if (this.foreground) {
            await promise;
        } else {
            promise;
        }
    }
}

function delay(duration) {
    return new Promise(resolve => setTimeout(resolve, duration));
}

One uses the code like this:

var player = new QBasicSound();
await player.play('T160O1L8CDEDCDL4ECC');

Note that you cannot start playing the sound directly, you need to wait for a user interaction first. An annoying rule to suppress annoying websites which would start playing the sound on load. And here is the result (press multiple times on Play for different melodies):

Javascript in modern times

There are two concepts that were used in this code that I want to discuss: named regular expression groups and async/await. Coincidentally, both are C# concepts that have crept up in the modern Javascript specifications when .NET developers from Microsoft started contributing to the language.

Named groups are something that appeared in ES2018 and it is something I've been using with joy in .NET and hated when I didn't have it in some other language. Look at the difference between the original design and the current one:

// original design
var match = /(a)bc/.exec('abcd');
if (match && match[1]) { /*do something with match[1]*/ }

// new feature
const match = /(?<theA>a)bc/.exec('abcd');
if (match && match.groups.theA) { /*do something with match.groups.theA*/ }

There are multiple advantages to this:

  • readability for people revisiting the code
  • robustness in the face of changes to the regular expression
    • the index might change if new groups are added to it
  • the code aligns with the C# code (I like that :) )

My advice is to always use named groups when using regular expressions.

Another concept is await/async. In .NET it is used to hide complex asynchronous interactions in the code and with the help of the compiler helps with all the tasks that are running at the same time. Unfortunately, in C#, that means polluting code with async keywords on all levels as async methods can only be used inside other async methods. No such qualms in Javascript.

While in .NET the await/async system runs over Task<T> methods, in Javascript it runs over Promises. Both are abstractions over work that is being done asynchronously.

A most basic example is this:

// original design
getSomethingAsync(url,function(data) {
  getSomethingElseAsync(data.url,function(data2) {
    // do something with data2
  }, errorHandler2);
},errorHandler1);

// Promises
getSomethingAsync(url)
  .then(function(data) {
    getSomethingElseAsync(data.url);
  })
  .then(function(data2) {
    // so something with data2
  })
  .catch(errorHandler);

// async/await
try {
  var data = await getSomethingAsync(url);
  var data2 = await getSomethingElseAsync(data.url);
  // do something with data2
} catch(ex) {
  errorHandler(ex);
}

You see that the await/async way looks like synchronous code, you can even catch errors. await can be used on any function that returns a Promise instance and the result of it is a non-blocking wait until the Promise resolves and returns the value that was passed to the resolve function.

If you go back to the QBasicSound class, at the end, depending on if the sound is in the foreground or background, the function is either awaiting a promise or ... just letting it run. You might also notice that I've added a delay function at the end of the code which is using setTimeout to resolve a Promise. Here is what is actually going on:

// using await
console.log(1);
await delay(1000).then(()=>console.log(2));
console.log(3);
// this logs 1,2,3


// NOT using await
console.log(1);
delay(1000).then(()=>console.log(2));
console.log(3);
// this logs 1,3,2

In the first case, the Promise that was constructed by a one second delay and then logging 2 is awaited, meaning the code waits for the result. After it is executed, 3 gets logged. In the second case, the logging of 2 is executed after one second delay, but the code does not wait for the result, therefore 3 is logged immediately and 2 comes after.

What sorcery is this?! Isn't Javascript supposed to be single threaded? How does it work? Well, consider that in the delay function, the resolve function will only be called after a timeout of one second. When executed, it starts the timeout, then reaches the end of the function. It has not been resolved yet, so it passes control back to the engine, which uses it to execute other things. When the timeout is fired, the engine takes back control, executes the resolve function, then passes control back. All of this is invisible to the user, who gets the illusion of multithreaded behavior.

Already some standard out of the box APIs are async, like fetch. In order to get an object from a REST API that is called via HTTP the code would look like this:

// fetch API
let response = await fetch('/article/promise-chaining/user.json');
let user = await response.json();

Conclusion

I spent an entire day learning about sounds and writing code that would emulate QBASIC code from a billion years ago. Who knows, maybe my next project will be to port the entire Gorillas game in Javascript. Now one can lovingly recreate the sounds of one's childhood.

Other references:

Gorillas.BAS

QBasic/Appendix

Generate Sounds Programmatically With Javascript

Musical Notes

Gorrilas game online