I've built an application and, like any lazy dev out there, I focused on the business logic, the project structure, the readability, comments, the dependency injection, the unit tests, you know... the code. My preference is to start from top to bottom, so I create more and more detailed implementations of interfaces while going down to the metal. The bottom of this chain is the repository, that class which handles database access, and I've spent little to understand or optimize that code. I mean, it's DB access, you read or you write stuff, how difficult can it be?

  When it was time to actually test it, the performance of the application was unexpectedly bad. I profiled it and I was getting reasonable percentages for different types of code, but it was all taking too long. And suddenly my colleague says "well, I tried a few things and now it works twice as fast". Excuse me?! You did WHAT?! I have been trying a few things too, and managed to do diddly squat! Give me that PR to see what you did! And... it was nothing I could see.

  He didn't change the code, he just added or altered the attributes decorating the properties of models. That pissed me off, because I had previously gone to the generated SQL with the SQL Profiler and it was all OK. So I executed my code and his code and recorded the SQL that came out:

  • was it the lazy loading? Nope. The number of instructions and their order was exactly the same
  • was it the explicit declaration of the names of indexes and foreign keys? Nope. Removing those didn't affect performance.
  • was it the ChangeTracker.LazyLoadingEnabled=false thing? Nope, I wasn't using child entities in a way that could be affected.
  • was there some other structure of the generated SQL? No. It was exactly the same SQL! Just my code was using thousands of CPU units and his was using none.
  • was it magic? Probably, because it made no sense whatsoever! Except...

Entity Framework generates simple SQL queries, but it doesn't execute them as you and I would. It constructs a string, then uses sp_executesql to run it. Something like this:

exec sp_executesql N'SELECT TOP(1) [p].[ID], [p].[TXT], [p].[LUP_TS]

FROM [sch].[table] AS [p]

WHERE [p].[ID] = @__p_0',N'@__p_0 nvarchar(64)',@__p_0='xxxx'

Do you see it? I didn't until I started to compare the same SQL in the two versions. And it was the type of the parameters! Note that the aptly named parameter @__p_0 is an NVARCHAR. The actual column in the database was VARCHAR! Meaning that the code above was unnecessarily always converting values in order to compare them. The waste of resources was staggering!

How do you declare the exact database type of your columns? Multiple ways. In my case there were three different problems:

  • no Unicode(false) attribute on the string columns - meaning EF expected the columns to be NVARCHAR
  • no Typename parameter in the Column attribute where the columns were NTEXT - meaning EF expected them to be NVARCHAR(Max)
    • I guess one could skip the Unicode thing and instead just specify the type name, but I haven't tested it
  • using MaxLength instead of StringLength - because even if their descriptions are very similar and MaxLength sounds like applying in more cases, it's StringLength that EF wants.

From 40-50ms per processing loop, it dropped to 21ms just by fixing these.

Long story short: parametrized SQL executed with sp_executesql hides a possible performance issue if the columns that you compare or extract have slightly different types than the one of the parameters.

Go figure. I hate Entity Framework!

Intro

  This post is about the System.InvalidOperationException: This SqlTransaction has completed; it is no longer usable. which may be because you shared your SqlConnection or you tried to SaveChanges twice and all of the other issues that you can google for. I was not so lucky. I spent a day and a half to understand what's going on and only with a help of another dev did I get close to the issue.

TL;DR;

I used a column with identity generation, but it wasn't also a primary key and EF sucks.

Details

  Imagine my scenario first: I wanted to use a database to assign a unique integer to a string. I was first searching for the entry in the DB and, if not found, I would just insert a new one. The SQL Server IDENTITY(1,1) setting would insure I got a new unique value for the inserted row. So the table would look like this:

CREATE TABLE STR_ID (
  STR NVARCHAR(64) PRIMARY KEY,
  ID INT IDENTITY(1,1)
}

Nothing fancy about this. Now for the C# part, using Entity Framework Core 6.

I created an entity class for it:

[Table("STR_ID")]
public class StrId {

  [Column("STR")]
  [Key]
  public string Text { get; set; }

  [Column("ID")]
  [DatabaseGenerated(DatabaseGeneratedOption.Identity)]
  public int Id { get; set; }

}

And then I proceeded to test it in the following way:

  • create a DbContext instance
  • search for a value by STR/Text in the proper DbSet
  • if it doesn't exist, insert a new row and SaveChanges
  • retrieve the generated id
  • dispose the context

I also ran this 20 times in parallel (well, as Tasks - a minor distinction, but it was using the thread pool).

The result was underwhelming. It would fail EVERY TIME, with either an exception about deadlocks or 

System.InvalidOperationException: This SqlTransaction has completed; it is no longer usable.
   at Microsoft.Data.SqlClient.SqlTransaction.ZombieCheck()
   at Microsoft.Data.SqlClient.SqlTransaction.Commit()

I did what every sane developer would do in this situation and bought myself a shotgun (we all know it's the most effective against zombies) then googled for other people having this issue. I mean, it would be common, right? You do some EF stuff in parallel and you get some errors.

No. This is happening in a parallelism scenario, but that's not the cause. Also, it's not about transactions. EF will wrap SaveChanges operations in a transaction and that is causing the error, but the transaction being completed is the issue and no, it's not your code!

I tried everything I could think of. I disabled the EF transaction and made my own, using all types of IsolationLevel, I tried EnableRetryOnFailure with hilarious results (I was monitoring the values inserted in the database with NOLOCK and they were going to 20, then back to 10, then 15, then back to 1 and it was taking ages trying to retry operations that apparently had dependencies to each other, only to almost all to fail after a long time). I even disabled connection pooling, which probably works, but would have made everything slow.

Solution

While I can't say what EXACTLY caused the problem (I would have to look into the Microsoft code and I don't feel like it now), the solution was ridiculously simple: just make the IDENTITY column a primary key instead:

CREATE TABLE STR_ID (
  ID INT PRIMARY KEY IDENTITY(1,1),
  STR NVARCHAR(64)
}

-- because this is what I am searching for
CREATE UNIQUE INDEX IX_STR_ID_STR ON STR_ID(STR) 
[Table("STR_ID")]
public class StrId {

  [Column("ID")]
  [Key]
  public int Id { get; set; }

  [Column("STR")]
  public string Text { get; set; }

}

I was about to use IsolationLevel.ReadUncommitted for the select or just set AutoTransactionsEnabled to false (which also would have solved the problem), when the other guy suggested I would use this solution. And I refused! It was dumb! Why the hell would that work? You dummy! And of course it worked. Why? Donno! The magical thinking in the design of EF strikes again and I am the dummy.

Conclusion

What happened is probably related to deadlocks, more specifically multiple threads trying to read/write/read again from a table and getting in each other's way. It probably has something to do with how IDENTITY columns need to lock the entire table, even if no one reads that row! But what it is certain to be is a bug: the database functionality for a primary key identity column and a unique indexed identity column is identical! And yet Entity Framework handles them very differently.

So, in conclusion:

  • yay! finally a technical post
  • this had nothing to do with how DbContexts get disposed (since in my actual scenario I was getting this from dependency injection and so I lost hours ruling that out)
  • the error about transactions was misleading, since the issue was what closed the transaction inside the Microsoft code not whatever you did
  • the advice of some of the AggregateExceptions up the stream (An exception has been raised that is likely due to a transient failure. Consider enabling transient error resiliency by adding 'EnableRetryOnFailure' to the 'UseSqlServer' call.) was even more misleading
  • the EF support for IDENTITY columns - well, it needs it because then how would it know not to attempt to save values in those columns - is also misleading, because it doesn't mean it's good support
  • while parallel access to the DB made the problem visible, it has little to do with parallelism 
  • EF knows how to handle PRIMARY KEYs so that's the solution
  • EF sucks!

I really hope this saves time for people in the same situation!

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C# 3.0 introduced Object Initializer Syntax which was a game changer for code that created new objects or new collections. Here is a contrived example:

var obj = new ComplexObject
{
    // object initializer
    AnItem = new Item("text1"),
    AnotherItem = new Item("text2"),
    // collection initializer
    RestOfItems = new List<Item>
    {
        new Item("text3"),
        new Item("text4"),
        new Item("text5")
    },
    // indexer initializer
    [0]=new Item("text6"),
    [1]=new Item("text7")
};

Before this syntax was available, the same code would have looked like this:

var obj = new ComplexObject();
obj.AnItem = new Item("text1");
obj.AnotherItem = new Item("text2");
obj.RestOfItems = new List<Item>();
obj.RestOfItems.Add(new Item("text3"));
obj.RestOfItems.Add(new Item("text4"));
obj.RestOfItems.Add(new Item("text5"));
obj[0] = new Item("text6");
obj[2] = new Item("text7");

It's not like the number of lines has changed, but both the writability and readability of the code increase with the new syntax. At least that's why I think. However, outside these very simple scenarios, the feature feels like it's encumbering us or that it is missing something. Imagine you want to only add items to a list based on some condition. You might get a code like this:

var list = new List<Item>
{
    new Item("text1")
};
if (condition) list.Add(new Item("text2"));

We use the initializer for one item, but not for the other. We might as well use Add for both items, then, or use some cumbersome syntax that hurts more than it helps:

var list = new[]
{
    new Item("text1"),
    condition?new Item("text2"):null
}
.Where(i => i != null)
.ToList();

It's such an ugly syntax that Visual Studio doesn't know how to indent it properly. What to do? Software patterns to the rescue! 

Seriously now, people who know me know that I scoff at the general concept of software patterns, but the patterns themselves are useful and in this case, even the conceptual framework that I often deride is useful here. Because we are trying to initialize an object or a collection, which means we are attempting to build it. So why not use a Builder pattern? Here are two versions of the same code, one with extension methods (which can be used everywhere, but might pollute the member list for common objects) and another with an actual builder object created specifically for our purposes (which may simplify usage):

// extension methods
var list = new List<Item>()
    .Adding(new Item("text1"))
    .ConditionalAdding(condition, new Item("text2"));
...
public static class ItemListExtensions
{
    public static List<T> Adding<T>(this List<T> list, T item)
    {
        list.Add(item);
        return list;
    }
    public static List<T> ConditionalAdding<T>(this List<T> list, bool condition, T item)
    {
        if (condition)
        {
            list.Add(item);
        }
        return list;
    }
}

// builder object
var list = new ItemListBuilder()
    .Adding("text1")
    .ConditionalAdding(condition, "text2")
    .Build();
...
public class ItemListBuilder
{
    private readonly List<Item> list;

    public ItemListBuilder()
    {
        list = new List<Item>();
    }

    public ItemListBuilder Adding(string text)
    {
        list.Add(new Item(text));
        return this;
    }

    public ItemListBuilder ConditionalAdding(bool condition, string text)
    {
        if (condition)
        {
            list.Add(new Item(text));
        }
        return this;
    }

    public List<Item> Build()
    {
        return list.ToList();
    }
}

Of course, for just a simple collection with some conditions this might feel like overkill, but try to compare the two versions of the code: the one that uses initializer syntax and then the Add method and the one that declares what it wants to do, step by step. Also note that in the case of the builder object I've taken the liberty of creating methods that only take string parameters then build the list of Item, thus simplifying the syntax and clarifying intent.

I had this situation where I had to map an object to another object by copying some properties into collections and values of some type to other types and so on. The original code was building the output using a top-down approach:

public Output BuildOutput(Input input) {
  var output=new Output();
  BuildFirstPart(output, input);
  BuildSecondPart(output, input);
  ...
  return output;
}

public BuildFirstPart(Output output, Input input) {
  var firstSection = BuildFirstSection(input);
  output.FirstPart=new List<Part> {
    new Part(firstSection)
  };
  if (condition) {
    var secondSection=BuildSeconfSection(input);
    output.FirstPart.Add(new Part(secondSection));
  }
}

And so on and so on. I believe that in this case a fluent design makes the code a lot more readable:

var output = new Output {
  FirstPart = new List<Part>()
    .Adding(BuildFirstSection(input))
    .ConditionalAdding(condition, BuildSecondSection(input),
  SecondPart = ...
};

The "build section" methods would also be inlined and replaced with fluent design methods. In this way the structure of "the output" is clearly shown in a method that declares what it will build and populates the various members of the Output class with simple calculations, the only other methods that the builder needs. A human will understand at a glance what thing it will build, see its structure as a tree of code and be able to go to individual methods to see or change the specific calculation that provides a value.

The point of my post is that sometimes the very out-of-the-box features that help us a lot most of the time end up complicating and obfuscating our code in specific situations. If the code starts to smell, to become unreadable, to make you feel bad for writing it, then stop, think of a better solution, then implement it so that it is the best version for your particular case. Use tools when they are useful and discard them when other solutions might prove more effective.

and has 1 comment

Intro

  Some of the most visited posts on this blog relate to dependency injection in .NET. As you may know, dependency injection has been baked in in ASP.Net almost since the beginning, but it culminated with the MVC framework and the .Net Core rewrite. Dependency injection has been separated into packages from where it can be used everywhere. However, probably because they thought it was such a core concept or maybe because it is code that came along since the days of UnityContainer, the entire mechanism is sealed, internalized and without any hooks on which to add custom code. Which, in my view, is crazy, since dependency injection serves, amongst other things, the purpose of one point of change for class instantiations.

  Now, to be fair, I am not an expert in the design patterns used in dependency injection in the .NET code. There might be some weird way in which you can extend the code that I am unaware of. In that case, please illuminate me. But as far as I went in the code, this is the simplest way I found to insert my own hook into the resolution process. If you just want the code, skip to the end.

Using DI

  First of all, a recap on how to use dependency injection (from scratch) in a console application:

// you need the nuget packages Microsoft.Extensions.DependencyInjection 
// and Microsoft.Extensions.DependencyInjection.Abstractions
using Microsoft.Extensions.DependencyInjection;
...

// create a service collection
var services = new ServiceCollection();
// add the mappings between interface and implementation
services.AddSingleton<ITest, Test>();
// build the provider
var provider = services.BuildServiceProvider();

// get the instance of a service
var test = provider.GetService<ITest>();

  Note that this is a very simplified scenario. For more details, please check Creating a console app with Dependency Injection in .NET Core.

Recommended pattern for DI

  Second of all, a recap of the recommended way of using dependency injection (both from Microsoft and myself) which is... constructor injection. It serves two purposes:

  1. It declares all the dependencies of an object in the constructor. You can rest assured that all you would ever need for that thing to work is there.
  2. When the constructor starts to fill a page you get a strong hint that your class may be doing too many things and you should split it up.

  But then again, there is the "Learn the rules. Master the rules. Break the rules" concept. I've familiarized myself with it before writing this post so that now I can safely break the second part and not master anything before I break stuff. I am talking now about property injection, which is generally (for good reason) frowned upon, but which one may want to use in scenarios adjacent to the functionality of the class, like logging. One of the things that always bothered me is having to declare a logger in every constructor ever, even if in itself a logger does nothing to the functionality of the class.

  So I've had this idea that I would use constructor dependency injection EVERYWHERE, except logging. I would create an ILogger<T> property which would be automatically injected with the correct implementation at resolution time. Only there is a problem: Microsoft's dependency injection does not support property injection or resolution hooks (as far as I could find). So I thought of a solution.

How does it work?

  Third of all, a small recap on how ServiceProvider really works.

  When one does services.BuildServiceProvider() they actually call an extension method that does new ServiceProvider(services, someServiceProviderOptions). Only that constructor is internal, so you can't use it yourself. Then, inside the provider class, the GetService method is using a ConcurrentDictionary of service accessors to get your service. In case the service accessor is not there, the method from the field _createServiceAccessor is going to be used. So my solution: replace the field value with a wrapper that will also execute our own code.

The solution

  Before I show you the code, mind that this applies to .NET 7.0. I guess it will work in most .NET Core versions, but they could change the internal field name or functionality in which case this might break.

  Finally, here is the code:

public static class ServiceProviderExtensions
{
    /// <summary>
    /// Adds a custom handler to be executed after service provider resolves a service
    /// </summary>
    /// <param name="provider">The service provider</param>
    /// <param name="handler">An action receiving the service provider, 
    /// the registered type of the service 
    /// and the actual instance of the service</param>
    /// <returns>the same ServiceProvider</returns>
    public static ServiceProvider AddCustomResolveHandler(this ServiceProvider provider,
                 Action<IServiceProvider, Type, object> handler)
    {
        var field = typeof(ServiceProvider).GetField("_createServiceAccessor",
                        BindingFlags.Instance | BindingFlags.NonPublic);
        var accessor = (Delegate)field.GetValue(provider);
        var newAccessor = (Type type) =>
        {
            Func<object, object> newFunc = (object scope) =>
            {
                var resolver = (Delegate)accessor.DynamicInvoke(new[] { type });
                var resolved = resolver.DynamicInvoke(new[] { scope });
                handler(provider, type, resolved);
                return resolved;
            };
            return newFunc;
        };
        field.SetValue(provider, newAccessor);
        return provider;
    }
}

  As you can see, we take the original accessor delegate and we replace it with a version that runs our own handler immediately after the service has been instantiated.

Populating a Logger property

  And we can use it like this to do property injection now:

static void Main(string[] args)
{
    var services = new ServiceCollection();
    services.AddSingleton<ITest, Test>();
    var provider = services.BuildServiceProvider();
    provider.AddCustomResolveHandler(PopulateLogger);

    var test = (Test)provider.GetService<ITest>();
    Assert.IsNotNull(test.Logger);
}

private static void PopulateLogger(IServiceProvider provider, 
                                    Type type, object service)
{
    if (service is null) return;
    var propInfo = service.GetType().GetProperty("Logger",
                    BindingFlags.Instance|BindingFlags.Public);
    if (propInfo is null) return;
    var expectedType = typeof(ILogger<>).MakeGenericType(service.GetType());
    if (propInfo.PropertyType != expectedType) return;
    var logger = provider.GetService(expectedType);
    propInfo.SetValue(service, logger);
}

  See how I've added the PopulateLogger handler in which I am looking for a property like 

public ILogger<Test> Logger { get; private set; }

  (where the generic type of ILogger is the same as the class) and populate it.

Populating any decorated property

  Of course, this is kind of ugly. If you want to enable property injection, why not use an attribute that makes your intention clear and requires less reflection? Fine. Let's do it like this:

// Add handler
provider.AddCustomResolveHandler(InjectProperties);
...

// the handler populates all properties that are decorated with [Inject]
private static void InjectProperties(IServiceProvider provider, Type type, object service)
{
    if (service is null) return;
    var propInfos = service.GetType()
        .GetProperties(BindingFlags.Instance | BindingFlags.Public)
        .Where(p => p.GetCustomAttribute<InjectAttribute>() != null)
        .ToList();
    foreach (var propInfo in propInfos)
    {
        var instance = provider.GetService(propInfo.PropertyType);
        propInfo.SetValue(service, instance);
    }
}
...

// the attribute class
[AttributeUsage(AttributeTargets.Property, AllowMultiple = false, Inherited = true)]
public class InjectAttribute : Attribute {}

Conclusion

I have demonstrated how to add a custom handler to be executed after any service instance is resolved by the default Microsoft ServiceProvider class, which in turn enables property injection, one point of change to all classes, etc. I once wrote code to wrap any class into a proxy that would trace all property and method calls with their parameters automatically. You can plug that in with the code above, if you so choose.

Be warned that this solution is using reflection to change the functionality of the .NET 7.0 ServiceProvider class and, if the code there changes for some reason, you might need to adapt it to the latest functionality.

If you know of a more elegant way of doing this, please let me know.

Hope it helps!

Bonus

But what about people who really, really, really hate reflection and don't want to use it? What about situations where you have a dependency injection framework running for you, but you have no access to the service provider builder code? Isn't there any solution?

Yes. And No. (sorry, couldn't help myself)

The issue is that ServiceProvider, ServiceCollection and all that jazz are pretty closed up. There is no solution I know of that solved this issue. However... there is one particular point in the dependency injection setup which can be hijacked and that is... the adding of the service descriptors themselves!

You see, when you do ServiceCollection.AddSingleton<Something,Something>, what gets called is yet another extension method, the ServiceCollection itself is nothing but a list of ServiceDescriptor. The Add* extensions methods come from ServiceCollectionServiceExtensions class, which contains a lot of methods that all defer to just three different effects:

  • adding a ServiceDescriptor on a type (so associating an type with a concrete type) with a specific lifetime (transient, scoped or singleton)
  • adding a ServiceDescriptor on an instance (so associating a type with a specific instance of a class), by default singleton
  • adding a ServiceDescriptor on a factory method (so associating a type with a constructor method)

If you think about it, the first two can be translated into the third. In order to instantiate a type using a service provider you do ActivatorUtilities.CreateInstance(provider, type) and a factory method that returns a specific instance of a class is trivial.

So, the solution: just copy paste the contents of ServiceCollectionServiceExtensions and make all of the methods end up in the Add method using a service factory method descriptor. Now instead of using the extensions from Microsoft, you use your class, with the same effect. Next step: replace the provider factory method with a wrapper that also executes stuff.

Since this is a bonus, I let you implement everything except the Add method, which I will provide here:

// original code
private static IServiceCollection Add(
    IServiceCollection collection,
    Type serviceType,
    Func<IServiceProvider, object> implementationFactory,
    ServiceLifetime lifetime)
{
    var descriptor = new ServiceDescriptor(serviceType, implementationFactory, lifetime);
    collection.Add(descriptor);
    return collection;
}

//updated code
private static IServiceCollection Add(
    IServiceCollection collection,
    Type serviceType,
    Func<IServiceProvider, object> implementationFactory,
    ServiceLifetime lifetime)
{
    Func<IServiceProvider, object> factory = (sp)=> {
        var instance = implementationFactory(sp);
        // no stack overflow, please
        if (instance is IDependencyResolver) return instance;
        // look for a registered instance of IDependencyResolver (our own interface)
        var resolver=sp.GetService<IDependencyResolver>();
        // intercept the resolution and replace it with our own 
        return resolver?.Resolve(sp, serviceType, instance) ?? instance;
    };
    var descriptor = new ServiceDescriptor(serviceType, factory, lifetime);
    collection.Add(descriptor);
    return collection;
}

All you have to do is (create the interface and then) register your own implementation of IDependencyResolver and do whatever you want to do in the Resolve method, including the logger instantiation, the inject attribute handling or the wrapping of objects, as above. All without reflection.

The kick here is that you have to make sure you don't use the default Add* methods when you register your services, or this won't work. 

There you have it, bonus content not found on dev.to ;)

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  So I was happily minding my own business after a production release only for everything to go BOOM! Apparently, maybe because of something we did, but maybe not, the memory of the production servers was running out. Exception looked something like:

System.OutOfMemoryException: Exception of type 'System.OutOfMemoryException' was thrown.
 at System.Reflection.Emit.TypeBuilder.SetMethodIL(RuntimeModulemodule, Int32tk ,BooleanisInitLocals, Byte[] body, Int32 bodyLength, 
    Byte[] LocalSig ,Int32sigLength, Int32maxStackSize, ExceptionHandler[] exceptions, Int32numExceptions ,Int32[] tokenFixups, Int32numTokenFixups)
 at System.Reflection.Emit.TypeBuilder.CreateTypeNoLock() 
 at System.Reflection.Emit.TypeBuilder.CreateType()
 at System.Xml.Serialization.XmlSerializationReaderILGen.GenerateEnd(String []methods, XmlMapping[] xmlMappings, Type[] types) 
 at System.Xml.Serialization.TempAssembly.GenerateRefEmitAssembly(XmlMapping []xmlMappings, Type[] types, StringdefaultNamespace ,Evidenceevidence)
 at System.Xml.Serialization.TempAssembly..ctor(XmlMapping []xmlMappings, Type[] types, StringdefaultNamespace ,Stringlocation, Evidenceevidence)
 at System.Xml.Serialization.XmlSerializer.GenerateTempAssembly(XmlMappingxmlMapping, Typetype ,StringdefaultNamespace, Stringlocation, Evidence evidence)
 at System.Xml.Serialization.XmlSerializer..ctor(Typetype, XmlAttributeOverrides overrides, Type[] extraTypes, 
     XmlRootAttributeroot, StringdefaultNamespace, Stringlocation, Evidence evidence)
 at System.Xml.Serialization.XmlSerializer..ctor(Typetype, XmlAttributeOverrides overrides) 

At first I thought there was something else eating away the memory, but the exception was repeatedly thrown at this specific point. And I did what every senior dev does: googled it! And I found this answer: "When an XmlSerializer is created, an assembly is dynamically generated and loaded into the AppDomain. These assemblies cannot be garbage collected until their AppDomain is unloaded, which in your case is never." It also referenced a Microsoft KB886385 from 2007 which, of course, didn't exist at that URL anymore, but I found it archived by some nice people.

What was going on? I would tell you, but Gergely Kalapos explains things much better in his article How the evil System.Xml.Serialization.XmlSerializer class can bring down a server with 32Gb ram. He also explains what commands he used to debug the issue, which is great!

But since we already know links tend to vanish over time (so much for stuff on the Internet living forever), here is the gist of it all:

  • XmlSerializer generates dynamic code (as dynamic assemblies) in its constructors
  • the most used constructors of the class have a caching mechanism in place:
    • XmlSerializer.XmlSerializer(Type)
    • XmlSerializer.XmlSerializer(Type, String)
  • but the others do not, so every time you use one of those you create, load and never unload another dynamic assembly

I know this is an old class in an old framework, but some of us still work in companies that are firmly rooted in the middle ages. Also since I plan to maintain my blog online until I die, it will live on the Internet for the duration.

Hope it helps!

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  Tracing and logging always seem simple, an afterthought, something to do when you've finished your code. Only then you realize that you would want to have it while you are testing your code or when an unexpected issue occurs in production. And all you have to work with is an exception, something that tells you something went wrong, but without any context. Here is a post that attempts to create a simple method to enhance exceptions without actually needing to switch logging level to Trace or anything like that and without great performance losses.

  Note that this is a proof of concept, not production ready code.

  First of all, here is an example of usage:

public string Execute4(DateTime now, string str, double dbl)
{
    using var _ = TraceContext.TraceMethod(new { now, str, dbl });
    throw new InvalidOperationException("Invalid operation");
}

  Obviously, the exception is something that would occur in a different way in real life. The magic, though, happens in the first line. I am using (heh!) the new C# 8.0 syntax for top level using statements so that there is no extra indentation and, I might say, one of the few situations where I would want to use this syntax. In fact, this post started from me thinking of a good place to use it without confusing any reader of the code.

  Also, TraceContext is a static class. That might be OK, since it is a very special class and not part of the business logic. With the new Roslyn source generators, one could insert lines like this automatically, without having to write them by hand. That's another topic altogether, though.

  So, what is going on there? Since there is no metadata information about the names of the currently executing method (without huge performance issues), I am creating an anonymous object that has properties with the same names and values as the arguments of the method. This is the only thing that might differ from one place to another. Then, in TraceMethod I return an IDisposable which will be disposed at the end of the method. Thus, I am generating a context for the entire method run which will be cleared automatically at the end.

  Now for the TraceContext class:

/// <summary>
/// Enhances exceptions with information about their calling context
/// </summary>
public static class TraceContext
{
    static ConcurrentStack<MetaData> _stack = new();

    /// <summary>
    /// Bind to FirstChanceException, which occurs when an exception is thrown in managed code,
    /// before the runtime searches the call stack for an exception handler in the application domain.
    /// </summary>
    static TraceContext()
    {
        AppDomain.CurrentDomain.FirstChanceException += EnhanceException;
    }

    /// <summary>
    /// Add to the exception dictionary information about caller, arguments, source file and line number raising the exception
    /// </summary>
    /// <param name="sender"></param>
    /// <param name="e"></param>
    private static void EnhanceException(object? sender, FirstChanceExceptionEventArgs e)
    {
        if (!_stack.TryPeek(out var metadata)) return;
        var dict = e.Exception.Data;
        if (dict.IsReadOnly) return;
        dict[nameof(metadata.Arguments)] = Serialize(metadata.Arguments);
        dict[nameof(metadata.MemberName)] = metadata.MemberName;
        dict[nameof(metadata.SourceFilePath)] = metadata.SourceFilePath;
        dict[nameof(metadata.SourceLineNumber)] = metadata.SourceLineNumber;
    }

    /// <summary>
    /// Serialize the name and value of arguments received.
    /// </summary>
    /// <param name="arguments">It is assumed this is an anonymous object</param>
    /// <returns></returns>
    private static string? Serialize(object arguments)
    {
        if (arguments == null) return null;
        var fields = arguments.GetType().GetProperties();
        var result = new Dictionary<string, object>();
        foreach (var field in fields)
        {
            var name = field.Name;
            var value = field.GetValue(arguments);
            result[name] = SafeSerialize(value);
        }
        return JsonSerializer.Serialize(result);
    }

    /// <summary>
    /// This would require most effort, as one would like to serialize different types differently and skip some.
    /// </summary>
    /// <param name="value"></param>
    /// <returns></returns>
    private static string SafeSerialize(object? value)
    {
        // naive implementation
        try
        {
            return JsonSerializer.Serialize(value).Trim('\"');
        }
        catch (Exception ex1)
        {
            try
            {
                return value?.ToString() ?? "";
            }
            catch (Exception ex2)
            {
                return "Serialization error: " + ex1.Message + "/" + ex2.Message;
            }
        }
    }

    /// <summary>
    /// Prepare to enhance any thrown exception with the calling context information
    /// </summary>
    /// <param name="args"></param>
    /// <param name="memberName"></param>
    /// <param name="sourceFilePath"></param>
    /// <param name="sourceLineNumber"></param>
    /// <returns></returns>
    public static IDisposable TraceMethod(object args,
                                            [CallerMemberName] string memberName = "",
                                            [CallerFilePath] string sourceFilePath = "",
                                            [CallerLineNumber] int sourceLineNumber = 0)
    {
        _stack.Push(new MetaData(args, memberName, sourceFilePath, sourceLineNumber));
        return new DisposableWrapper(() =>
        {
            _stack.TryPop(out var _);
        });
    }

    /// <summary>
    /// Just a wrapper over a method which will be called on Dipose
    /// </summary>
    public class DisposableWrapper : IDisposable
    {
        private readonly Action _action;

        public DisposableWrapper(Action action)
        {
            _action = action;
        }

        public void Dispose()
        {
            _action();
        }
    }

    /// <summary>
    /// Holds information about the calling context
    /// </summary>
    public class MetaData
    {
        public object Arguments { get; }
        public string MemberName { get; }
        public string SourceFilePath { get; }
        public int SourceLineNumber { get; }

        public MetaData(object args, string memberName, string sourceFilePath, int sourceLineNumber)
        {
            Arguments = args;
            MemberName = memberName;
            SourceFilePath = sourceFilePath;
            SourceLineNumber = sourceLineNumber;
        }
    }
}

Every call to TraceMethod adds a new MetaData object to a stack and every time the method ends, the stack will pop an item. The static constructor of TraceMethod will have subscribed to the FirstChangeException event of the current application domain and, whenever an exception is thrown (caught or otherwise), its Data dictionary is getting enhanced with:

  • name of the method called
  • source file name
  • source file line number where the exception was thrown.
  • serialized arguments (remember Exceptions need to be serializable, including whatever you put in the Data dictionary, so that is why we serialize it all)

(I have written another post about how .NET uses code attributes to get the first three items of information during build time) 

This way, you get information which would normally be "traced" (detailed logging which is usually detrimental to performance) in any thrown exception, but without filling some trace log or having to change production configuration and reproduce the problem again. Assuming your application does not throw exceptions all over the place, this adds very little complexity to the executed code.

Moreover, this will enhance exception with the source code file name and line number even in Release mode!

I am sure there are some issues with code that might fail and it is not caught in a try/catch and of course the serialization code is where people should put a lot of effort, since different types get to be serialized for inspection differently (think async methods and the like). And more methods should be added so that people trace whatever they like in thrown exceptions. Yet, as I said, this is a POC, so I hope it gets you inspired.

and has 0 comments

I got this exception at my work today, a System.ArgumentException with the message "Argument passed in is not serializable.", that I could not quite understand. Where does it come from, since the .NET source repository does not contain the string? How can I fix it?

The stack trace ended up at System.Collection.ListDictionaryInternal.set_Item(Object key, Object value) in a method where, indeed, I was setting a value in a dictionary. But this is not how dictionaries behave! The dictionary in question was the Exception.Data property. It makes sense, because Exception objects are supposed to be serializable, and I was adding a value of type HttpMethod which, even if extremely simple and almost always used as an Enum, it is actually a class of its own which is not serializable!

So, there you have it, always make sure you add serializable objects in an exception's Data dictionary.

But why is this happening? The implementation of the Data property looks like this:

public virtual IDictionary Data { 
  [System.Security.SecuritySafeCritical]
  get {
    if (_data == null)
      if (IsImmutableAgileException(this))
        _data = new EmptyReadOnlyDictionaryInternal();
      else
        _data = new ListDictionaryInternal();
    return _data;
  }
}

Now, EmptyReadOnlyDictionaryInternal is just a dictionary you can't add to. The interesting class is ListDictionaryInternal. Besides being an actual linked list implementation (who does that in anything but C++ classrooms?) it contains this code:

#if FEATURE_SERIALIZATION
  if (!key.GetType().IsSerializable)                 
    throw new ArgumentException(Environment.GetResourceString("Argument_NotSerializable"), "key");                    
  if( (value != null) && (!value.GetType().IsSerializable ) )
    throw new ArgumentException(Environment.GetResourceString("Argument_NotSerializable"), "value");                    
#endif

So both key and value of the Data dictionary property in an Exception instance need to be serializable.

But why didn't I find the string in the source reference? While the Microsoft reference website doesn't seem to support simple string search, it seems Google does NOT index the code GitHub pages either. You have to:

  • manually go to GitHub and search
  • get no results
  • notice that the "Code" section of the results has a question mark instead of a number next to it
  • click on it
  • then it asks you to log in
  • and only then you get results!

So bonus thing: if you are searching for some string in the .NET source code, first of all use the GitHub repo, then make sure you log in when you search.

Intro

Dependency injection is baked in the ASP.Net Core projects (yes, I still call it Core), but it's missing from console app templates. And while it is easy to add, it's not that clear cut on how to do it. I present here three ways to do it:

  1. The fast one: use the Worker Service template and tweak it to act like a console application
  2. The simple one: use the Console Application template and add dependency injection to it
  3. The hybrid: use the Console Application template and use the same system as in the Worker Service template

Tweak the Worker Service template

It makes sense that if you want a console application you would select the Console Application template when creating a new project, but as mentioned above, it's just the default template, as old as console apps are. Yet there is another default template, called Worker Service, which almost does the same thing, only it has all the dependency injection goodness baked in, just like an ASP.Net Core Web App template.

So start your Visual Studio, add a new project and choose Worker Service:

It will create a project containing a Program.cs, a Worker.cs and an appsettings.json file. Program.cs holds the setup and Worker.cs holds the code to be executed.

Worker.cs has an ExecuteAsync method that logs some stuff every second, but even if we remove the while loop and add our own code, the application doesn't stop. This might be a good thing, as sometimes we just want stuff to work until we press Ctrl-C, but it's not a console app per se.

In order to transform it into something that works just like a console application you need to follow these steps:

  1. inject an IHost instance into your worker
  2. specifically instruct the host to stop whenever your code has finished

So, you go from:

public class Worker : BackgroundService
{
    private readonly ILogger<Worker> _logger;

    public Worker(ILogger<Worker> logger)
    {
        _logger = logger;
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        while (!stoppingToken.IsCancellationRequested)
        {
            _logger.LogInformation("Worker running at: {time}", DateTimeOffset.Now);
            await Task.Delay(1000, stoppingToken);
        }
    }
}

to:

public class Worker : BackgroundService
{
    private readonly ILogger<Worker> _logger;
    private readonly IHost _host;

    public Worker(ILogger<Worker> logger, IHost host)
    {
        _logger = logger;
        _host = host;
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        Console.WriteLine("Hello world!");
        _host.StopAsync();
    }
}

Note that I did not "await" the StopAsync method because I don't actually need to. You are telling the host to stop and it will do it whenever it will see fit.

If we look into the Program.cs code we will see this:

public class Program
{
    public static void Main(string[] args)
    {
        CreateHostBuilder(args).Build().Run();
    }

    public static IHostBuilder CreateHostBuilder(string[] args) =>
        Host.CreateDefaultBuilder(args)
            .ConfigureServices((hostContext, services) =>
            {
                services.AddHostedService<Worker>();
            });
}

I don't know why they bothered with creating a new method and then writing it as an expression body, but that's the template. You see that there is a lambda adding dependencies (by default just the Worker class), but everything starts with Host.CreateDefaultBuilder. In .NET source code, this leads to HostingHostBuilderExtensions.ConfigureDefaults, which adds a lot of stuff:

  • environment variables to config
  • command line arguments to config (via CommandLineConfigurationSource)
  • support for appsettings.json configuration
  • logging based on operating system

That is why, if you want these things by default, your best bet is to tweak the Worker Service template

Add Dependency Injection to an existing console application

Some people want to have total control over what their code is doing. Or maybe you already have a console application doing stuff and you just want to add Dependency Injection. In that case, these are the steps you want to follow:

  1. create a ServiceCollection instance (needs a dependency to Microsoft.Extensions.DependencyInjection)
  2. register all dependencies you want to use to it
  3. create a starting class that will execute stuff (just like Worker above)
  4. register starting class in the service collection
  5. build a service provider from the collection
  6. get an instance of the starting class and execute its one method

Here is an example:

class Program
{
    static void Main(string[] args)
    {
        var services = new ServiceCollection();
        ConfigureServices(services);
        services
            .AddSingleton<Executor,Executor>()
            .BuildServiceProvider()
            .GetService<Executor>()
            .Execute();
    }

    private static void ConfigureServices(IServiceCollection services)
    {
        services
            .AddSingleton<ITest, Test>();
    }
}

public class Executor
{
    private readonly ITest _test;

    public Executor(ITest test)
    {
        _test = test;
    }

    public void Execute()
    {
        _test.DoSomething();
    }
}

The only reason we register the Executor class is in order to get an instance of it later, complete with constructor injection support. You can even make Execute an async method, so you can get full async/await support. Of course, for this example appsettings.json configuration or logging won't work until you add them.

Mix them up

Of course, one could try to get the best of both worlds. This would work kind of like this:

  1. use Host.CreateDefaultBuilder() anyway (needs a dependency to Microsoft.Extensions.Hosting), but in a normal console app
  2. use the resulting service provider to instantiate a starting class
  3. start it

Here is an example:

class Program
{
    static void Main(string[] args)
    {
        Host.CreateDefaultBuilder()
            .ConfigureServices(ConfigureServices)
            .ConfigureServices(services => services.AddSingleton<Executor>())
            .Build()
            .Services
            .GetService<Executor>()
            .Execute();
    }

    private static void ConfigureServices(HostBuilderContext hostContext, IServiceCollection services)
    {
        services.AddSingleton<ITest,Test>();
    }
}

The Executor class would be just like in the section above, but now you get all the default logging and configuration options from the Worker Service section.

Conclusion

What the quickest and best solution is depends on your situation. One could just as well start with a Worker Service template, then tweak it to never Run the builder and instead configure it as above. One can create a Startup class, complete with Configure and ConfigureServices as in an ASP.Net Core Web App template or even start with such a template, then tweak it to work as a console app/web hybrid. In .NET Core everything is a console app anyway, it's just depends on which packages you load and how you configure them.

Learning from React series:

  • Part 1 - why examining React is useful even if you won't end up using it
  • Part 2 - what Facebook wanted to do with React and how to get a grasp on it
  • Part 3 - what is Reactive Programming all about?
  • Part 4 - is React functional programming?
  • Part 5 - Typescript, for better and for worse
  • Part 6 (this one) - Single Page Applications are not where they wanted to be

We cannot discuss React without talking about Single Page Applications, even if one can make a React based web site that isn't a SPA and SPAs that don't use a framework or library. What are SPAs? Let's start with what they are not.

SPAs are not parallax background, infinite scroll pages where random flashy things jump at you from the top and bottom and the sides like in a bloody ghost train ride! If you ever considered doing that, this is my personal plea for you to stop. For the love of all that is decent, don't do it!

SPAs are desktop applications for the web. They attempt to push the responsive, high precision actions, high CPU usage and fancy graphics to the client while maintaining the core essentials on the server, like security and sensitive data, while trying to assert full control over the interface and execution flow. In case connectivity fails, the cached data allows the app to work just fine offline until you reconnect or you need uncached data. And with React (or Angular and others), SPAs encapsulate UI in components, just like Windows Forms.

You know who tried (and continues to try) to make Windows Forms on the web? Microsoft. They started with ASP.Net Web Forms, which turned into ASP.Net MVC, which turned into ASP.Net Web API for a while, then turned to Blazor. At their heart, all of these are attempts to develop web applications like one would desktop applications.

And when they tried to push server side development models to the web they failed. They might succeed in the future and I wish them all the luck, but I doubt Microsoft will make it without acknowledging the need to put web technologies first and give developers full and direct access to the browser resources.

Ironically, SPAs (and modern web development in general) put web technologies first to a degree that makes them take over functionality already existing in the browser, like location management, URL handling and rendering components, but ignore server technologies.

It is relevant to make the comparison between SPAs and desktop applications because no matter how much they change browsers to accommodate this programming style, there are fundamental differences between the web and local systems.

For one, the way people have traditionally been trained to work on the web is radically different from how modern web development is taught.

Remember Progressive Enhancement? It was all about serving as much of the client facing, relevant content to the browser first, then enhancing the page with Javascript and CSS. It started from the idea that Javascript is slow and might not be enabled. Imagine that in 2021! When first visiting a page you don't want to keep the users waiting for all the fancy stuff to load before they can do anything. And SEO, even if nowadays the search engine(s?) know how to execute Javascript to get the content as a user would, still cares a lot about the first load experience.

Purely client tools like React, Angular, Vue, etc cannot help with that. All they can do is optimize the Javascript render performance and hope for the best. There are solutions cropping up: check out SSR and ReactDomServer and React Server Components. Or Astro. Or even Blazor. The takeaway here is that a little bit of server might go a long way without compromising the purity of the browser based solution.

Remember jQuery and before? The whole idea back then was to access the DOM as a singular UI store and select or make changes to any element on the entire page. Styling works the same way. Remember CSS Zen Garden? You change one global CSS file and your website looks and feels completely different. Of course, that comes with horrid things like CSS rule precedence or !important [Shudder], yet treating the page as a landscape that one can explore and change at will is a specifically browser mindset. I wasn't even considering the possibility when I was doing Windows Forms.

In React, when I was thinking of a way to add help icons to existing controls via a small script, the React gurus told me to not break encapsulation. That was "not the way". Well, great, Mandalorian! That's how you work a lot more to get to the same thing we have done for years before your way was even invented! In the end I had to work out wrapper elements that I had to manually add to each form control I wanted to enhance.

In the same app I used Material Design components, which I thought only needed a theme to change the way they look and feel, only to learn that React controls have to be individually styled and that the theme itself controls very few things. Even if there is support for theming, if you want to significantly change the visuals and behaviour you will have to create your own controls that take what they need (much more than what Material UI controls do) from the theme provider.

A local desktop application is supposed to take most of the resources that are available to it. You can talk about multitasking all you want, but normal people focus on one complex application at a time. At its core a SPA is still a browser tab, using one thread. That means even with the great performance of React, you still get only one eighth (or something, based on the number of processors) from the total computer resources. There are ways of making an application use multiple threads, but that is not baked in React either. Check out Neo.js for an attempt to do just that.

You can't go too far in the other direction either. Web user experience is opening many tabs and switching from one to the other, refreshing and closing and opening others and even closing the browser with all the tabs open or restoring an entire group of bookmarks at once. And while we are at the subject of URLs and bookmarks, you will find that making a complex SPA consistently alter the address location so that a refresh or a bookmark gets you to the same place you were in is really difficult.

A local Windows app usually has access to a lot of the native resources of the computer. A browser is designed to be sandboxed from them. Moreover, some users don't have correct settings or complete access to those settings, like in corporate environments for example. You can use the browser APIs, but you can't fully rely on them. And a browser tab is subject to firewall rules and network issues, local policies, browser extensions and ad blockers, external ad providers and so on.

You may think I am taking things to an unreasonable extreme. You will tell me that the analogy to desktop apps breaks not despite, but because of all of the reasons above and thus SPAs are something else, something more light, more reusable, webbier, with no versioning issues and instant access and bookmarkable locations. You will tell me that SPAs are just normal web sites that work better, not complex applications. I will cede this point.

However! I submit that SPAs are just SPAs because that's all they could be. They tried to replace fully fledged native apps and failed. That's why React Native exists, starting as a way to do more performant apps for mobiles and now one can write even Windows applications with it.

Single Page Applications are great. I am sure they will become better and better with time until we will forget normal HTML pages exist and that servers can render and so on. But that's going in the wrong direction. Instead of trying to emulate desktop or native apps, SPAs should embrace their webbiness.

Is Javascript rendering bad? No. In fact it's just another type of text interpreted by the browser, just like HTML would be, but we can do better.
Is Javascript URL manipulation bad? No. It's the only way to alter the address location without round trips to the server, but sometimes we need the server. Perhaps selective loading of component resources and code as needed will help.
Is single threaded execution bad? No, but we are not restricted to it.
Is component encapsulation bad? Of course not, as long as we recognize that in the end it will be rendered in a browser that doesn't care about your encapsulation.
The only thing that I am still totally against is CSS in Javascript, although I am sure I haven't seen the best use of it yet.

React is good for SPAs and SPAs are good for React, but both concepts are trying too hard to take things into a very specific direction, one that is less and less about the browser and more about desktop-like components and control of the experience. Do I hate SPAs? No. But as they are now and seeing where they are going, I can't love them either. Let's learn from them, choose the good bits and discard the chaff.  

  Learning from React series:

  • Part 1 - why examining React is useful even if you won't end up using it
  • Part 2 - what Facebook wanted to do with React and how to get a grasp on it
  • Part 3 - what is Reactive Programming all about?
  • Part 4 - is React functional programming?
  • Part 5 (this one) - Typescript, for better and for worse
  • Part 6 - Single Page Applications are not where they wanted to be

  Typescript is a programming language developed by Microsoft. It is a superset of Javascript that allows a lot of type checking and manipulation, hence the name. React and Vue fully support it while Angular requires it. So what is the reason for the adoption of this new language? What are its advantages and disadvantages?

  First of all, what is it? I would start metaphorically, if you can forgive that. Imagine a vast jungle, grown organically since time immemorial, chaotic and wild. Many developers went in, but few have come out unscathed, some never to be seen again. That's Javascript for you. It was released in 1995 as a basic scripting language for browsers, but it was designed as so flexible and complete that it could be used as a programming language in any context with minor modifications. For a very long time tightly coupled with its (very inefficient) browser implementations, it was dismissed from being a proper programming language. But that ended pretty much when V8 was launched, a performant Javascript engine that could be used separately to run the language in whatever situation the developer wanted. With V8, Chrome was launched and soon enough Node.js, which ran Javascript on the server as a proper language.

  The worst and best feature of Javascript is flexibility. You can do pretty much whatever you want in it, as it is a dynamic language unencumbered by such silly things as encapsulation, classes, types and so on. So if you started in a structured way, you could do a lot, if not - like most people unfamiliar with the language - you created a mess that no one could understand, including yourself. So if Javascript is a jungle, Typescript is Duke Nukem coming to cut the trees, wall off vast swathes of forest and only allow a narrow path for life to exist. Only, on that narrow path you get the same chaotic and wild proliferation. A lot fewer software developers traverse the forest and come out with PTSD, but a lot more people go through than before and mistakes can and will be made.

  I guess what I am trying to say is that Typescript sometimes feels like a square peg forced into a round hole. It is not a bad language. In fact, it is amazing in some parts. The type system introduced by Microsoft acts like a kind of system of annotations that inform on what you are actually doing. Tools are aware now of the types of values you use, can optimize code, find errors, warn devs, autocomplete code, help with development, etc. And I am willing to bet that people working on the language are having the time of their lives, because it has to be fun to work on abstract computer science and getting paid, too.

  But what does that mean for the frontend industry? It means that people are getting pushed on that narrow jungle path, for better or for worse. As a small business, you will have to either accept a shitty website created by cheap Javascript and vanilla HTML cavemen or get a lot out of your pocket to hire people who spend time and effort to understand Typescript and some, if not most, of the frontend frameworks that are fashionable at the moment. As a large company you will get tectonic shifts in technology, leaving a large part of your workforce in limbo, while having to spend a lot on hiring and redesigning flows. As an industry, we become dependent on several companies that spend the effort of keeping their frameworks up to date and documented. 

  Let me give you some Typescript questions (that I will not answer) to test your knowledge:

  • can you tell me what all of these types are and how they differ from each other: undefined, null, any, unknown, never, void ?
  • how can you tell if a Typescript object is of a specific form (the equivalent of the .NET 'is' or 'as' functionality)?
  • what is the difference between a union of literal types and an enum?
  • what are and how can you use BigInt, ReadOnlyArray, Partial, NonNullable, Required?
  • what is the difference between a private member of a Typescript class and one starting with #?
  • do you know how to use unions in interpolated strings?
  • what is the difference between interface, type, class, type intersection, class expression and module?

 I could go on and on. On how the possibility of null is now something you have to declare explicitly, for example. I didn't (dare to) ask about type guards and how narrowing works and what conditional types are. And there are so many gotchas for developers coming from other languages, because the language features have been added by people who worked on C#, so they are kind of the same, but actually not. Type meaning and conversion is a large bit of confusing difference between Typescript and C#/Java. For example you can define a class and then cast some data to it, but you don't get what you expect:

class MyClass {
  public name: string='';
  public sayHello() { console.log(`Hello ${this.name}`); }
}

const my:MyClass = { name: 'Siderite' } as MyClass;
console.log(my); // { "name": "Siderite" }
console.log(typeof(my)); // "object"
console.log(my instanceof MyClass) // false
console.log(my.sayHello()); // ERR: my.sayHello is not a function 

There are still web sites dedicated to the inconsistencies of Javascript. Typescript doesn't solve these issues, it mostly hides them. I am sure it's fun to play with types, but is that the optimal solution for the problem at hand, mainly the many ways you can do Javascript wrong? I would argue no. It's fun to work in, but there is a clear dependency between Typescript and Javascript, which forced so many changes in Typescript from Javascript and the other way around, as they have to be kept in sync. All while Javascript needs to remain backwards compatible, too.

"But what about React? Weren't you talking about that, Siderite?"

Yes, I was. I only looked deeper into Typescript because I did this project in React. Before, I had used it with Angular and frankly I didn't feel the friction that I felt now. Angular is designed with Typescript in mind, the development experience is smoother. Angular also uses two directional bindings to propagate changes and that means less Typescript code. The only code you actually need to write is network API code, for which you have out of the box HTTP services, and some limited interface logic. React doesn't do that.

First of all, React has been designed within a kind of declarative/functional mindset, as I explained in previous chapters of this series. It focuses a lot on immutability and functions that are passed around and declaring what your expectations are. Typescript is fundamentally an imperative language. After forcing it through the round hole, the square peg now has to go through a triangular hole, too. The immutability forces one to use a lot of code for changes coming from the UI towards the Typescript logic.

Then, React is a library. It was designed as such and has less levers to force the developer in a direction or another. Even when following a clear development strategy, there are many of which to choose from, all tried and tested and valid, but very different from one another. The jungle was tamed, but now you must consider a multiverse of jungles, each with a different shape.

Finally, React started out in Javascript. Many documentation pages are still just about Javascript. New innovations in the field of React are developed and tested out independently, by various people with various skills and motivations. The learning curve is not steep, but the paths are many.

So in the end, Typescript is an interesting experiment in programming languages, one that will probably surprise me in the near future with ideas that can only be implemented using it. However it is not perfect and its dependency on Javascript is unfortunate, even if its inspiration was not. The purpose of the language was to guide and help developers mired in Javascript confusion, but using it with React goes against that very purpose, as React is still something relatively new and evolving wildly in all directions, so React doesn't help Typescript. Does Typescript help React? I would say yes. However I don't feel that it is enough in its current form. The friction between the two concepts is palpable and I dare any of you to prove me wrong.

It seems I've talked a lot about the problems of React rather than its benefits. I blamed it on things ranging from confusing and obsolete documentation to inconsistent goals of the library and underlying programming language. That's the way I work, focusing on problems so I can find one I can fix. In the next chapter I want to discuss about React in the wild and what are the good things people are saying about it. The most interesting question however, the one that I want to answer with this entire series, is how can we improve our work by adapting lessons learned, either from React to whatever we do or the other way around. What concrete ideas should we adopt from React and which we should condemn to the pit of failed concepts?

  Learning from React series:

  • Part 1 - why examining React is useful even if you won't end up using it
  • Part 2 - what Facebook wanted to do with React and how to get a grasp on it
  • Part 3 - what is Reactive Programming all about?
  • Part 4 (this one) - is React functional programming?
  • Part 5 - Typescript, for better and for worse
  • Part 6 - Single Page Applications are not where they wanted to be

  React was designed just when classes and modules were making their way into Javascript, so it made sense to use them. Developers that are not coming from the Javascript or dynamic languages world are used to the type safety and hierarchical structure that classes provide. And it also made sense from the standpoint of the product. If you want to encapsulate state, logic and presentation why not used existing functioning models like classes, components and so on.

  However, at the same time ideas like functions being first class citizens of programming languages and functional programming were making a comeback, mostly because of big data. That meant that lambdas (arrow functions) were popping up everywhere. If you are a C# developer, you already are familiar with them. Something like Func<int,int> func = (int x)=> x*2; represents a lambda function, which is the same as something written like private int f2(int x) { return x*2; }, yet lambda functions can be declared inside code blocks, can be implicitly cast to Expressions and manipulated and they are brilliant as method parameters. Check out the lambda version in C# compared to the function version in VB:

// C#
var items = allItems.Where(i=>!i.deleted);
// C# function body
var items = allItems.Where(i=>{
                             return !i.deleted
                           });
// VB
Dim items = allItems.Where(Function(i) Not i.deleted)
// VB function body
Dim items = allItems.Where(Function(i) 
			      Return Not i.deleted
			   End Function)

 Similarly, Javascript had only function syntax, even if functions were designed to be first class citizens of the language since its inception. Enter arrow functions in Javascript:

// before
var self = this;
var items = allItems.filter(function(i) {
  return self.validate(i);
});

// after
var items = allItems.filter(i=>this.validate(i));

Note how arrow functions don't have an internal 'this' so you don't need to bind functions or create self variables.

So at this point, React changed and instead of classes, they implemented "functional syntax" in React Hooks. Behind the scenes a component is still generated as a class which React uses and the old syntax is still valid. For example at this time there is no way to create an error boundary component using functional syntax. The result is a very nice simplification of the code:

// React classic (pardon the pun)
export class ShowCount extends React.Component {
  constructor(props) {
    super(props);
    this.state = {
      count: 0
    };
  }
  componentDidMount() {
    this.setState({
      count: this.props.count
    })
  }

  render() {
    return (
      <div> 
        <h1> Count : {this.state.count} </h1>
      </div>
    );
  }
}

// React Hooks
export function ShowCount(props) {
  const [count, setCount] = useState();

  useEffect(() => {
    setCount(props.count);
  }, [props.count]);

  return (
    <div>
      <h1> Count : {count} </h1>
    </div>
  );
}

// courtesy of https://blog.bitsrc.io/6-reasons-to-use-react-hooks-instead-of-classes-7e3ee745fe04

  But this does not just provide a better syntax, it also changes the way development is done. Inheritance is basically eliminated in favor of composition and people are starting to use the word "functional" in sentences uttered in the real world. And while the overall design of React to use unidirectional binding and immutable variables was there since inception, I do feel like this is just one more step towards a functional programming approach and the reason for so many functional purists popping up lately.

  What is functional programming, though? Wikipedia defines it as "a declarative programming paradigm in which function definitions are trees of expressions that map values to other values, rather than a sequence of imperative statements which update the running state of the program." Sound familiar?

  I will have you know that I have friends that have rebelled and gone to the other side, making applications (including UI) with F# and refusing to submit to the Galactic Imperative. After playing with React I can say that I understand why this approach has appeal. One declares what they need, ignore flow and constrain their efforts inside components that are more or less independent. A program looks and feels like a big function that uses other functions and to which you just provide inputs and out comes UI ready to use. If the same input is provided, the same output results. You can test it to perfection, you can infer what happens with an entire tree of such functions and make optimizations in the transpiler without changing the code. You can even use a diff algorithm on the output tree and just update what changed in the UI.

  But it is time to call bullshit. We've used functions that receive pure data on one side and output user interface on the other side since forever. They are called views. One could even argue that an API is a data provider and the application is the function that uses the data to output UI. You don't ignore flow, you move it up! You will still have to model the interactions between every piece of data you have and all the events that come in. One might even say the unforgivable and assert that React is just another Model-View thingie with the extra constraint that it will forcibly re-render a component when its input state changes.

  That is my main takeaway from React: the idea that forcing re-rendering of components forces the developer to move the state up, closer to where it should be. No one can store stuff in browser variables, in element attributes and data, because all of it will be lost on next render. That is good news, but also very bad news. Let me get you through an example:

  We have data that we need shown in a grid. Every row has an expand/collapse button that will show another grid under it, with details related to that row. The React way of doing things would take us through these steps:

  • create a component that represents the grid and receives an array as input
  • it will contain code that maps the array to a list of row components which receive each row as the input
  • the row component will render a button that will dispatch an expand event for the row when clicked
  • on click the row expanded state will be changed and the data for the row detail grid retrieved

  It sounds great, right? OK, where do you store the state of row expansion? How do we push it to the row component? Let's use a map/dictionary of row id and boolean, why don't we? Does that mean that when you expand/collapse a row only the boolean changes or the entire structure? What will get re-rendered? The row component in question or all the row components?

  What happens when we go to the next page in the grid and then go back? Should we return to the same row expansion states? Where should the scrollbar in the grid be? Should we keep that in the state as well and how do we push it to the grid component? Do row details grids have scroll? Doesn't the size of each component affect the scroll size, so how do we store the scroll position? What is the user resizes the browser or zooms in or out?

  What happens when we resize a grid column? Doesn't that mean that all row components need to be re-rendered? If yes, why? If no, why? What if you resize the column of a detail grid? Should all detail grids have the same resizing applied? How do you control which does what?

  Many grids I've seen are trying to store the expansion, the details, everything in the object sent as a parameter to the row. This seems reasonable until you realize that adding anything to the object changes it, so it should trigger a re-render. And then there is Typescript, which expects an object to keep to its type or else you need to do strange casts from something you know to "unknown", something that could be anything. That's another story, though.

  Suddenly, the encapsulation of components doesn't sound so great anymore. You have to keep count of everything, everywhere, and this data cannot be stored inside the component, but outside. Oh, yes, the component does take care of its own state, but you lose it when you change the input data. In fact, you don't have encapsulation in components, but in pairs of data (what React traditionally calls props) and component. And the props must change otherwise you have a useless component, therefore the data is not really immutable and the façade of functional programming collapses.

  There are ways of controlling when a component should update, but this is not a React tutorial, only a lessons learned blog post. Every complexity of interaction that you have ever had in a previous programming model is still there, only pushed up, where one can only hope it is completely decoupled from UI, to which you add every quirk and complexity coming from React itself. And did we really decouple UI or did we break it into pieces, moving the simplest and less relevant one out and keeping the messy and complex one that gave us headaches in the first place in? It feels to me like React is actually abstracting the browser from you, rather than decoupling it and letting the developer keep control of it.

  After just a month working in this field I cannot tell you that I understood everything and have all the answers, but my impression as of now is that React brings very interesting ideas to the table, yet there is still a lot of work to be done to refine them and maybe turn them into something else.

  Next time I will write about Typescript and how it helps (and hinders) React and maybe even Angular development. See you there!

 Learning from React series:

  • Part 1 - why examining React is useful even if you won't end up using it
  • Part 2 - what Facebook wanted to do with React and how to get a grasp on it
  • Part 3 (this one) - what is Reactive Programming all about?
  • Part 4 - is React functional programming?
  • Part 5 - Typescript, for better and for worse
  • Part 6 - Single Page Applications are not where they wanted to be

The name React is already declaring that it is used in reactive programming, but what is that? Wikipedia is defining it as "a declarative programming paradigm concerned with data streams and the propagation of change". It expands on that to say that it declares the relationship between elements and updates them when either change. You can easily imagine a graph of elements magically updating as any of them changes. However, the implementation details of that magic matter.

  In 2011 Microsoft revealed a free .Net library called Reactive Extensions, or ReactiveX or RX. It was based on a very interesting observation that the observer/observable patterns are the mirror images of iterator/iterable. When the iterator moves through an iterable, the observer reacts to events in the observable; one is imperative, the other reactive. The library was so popular that it was immediately adopted for a bunch of programming languages, including Javascript. It also allowed for operations traditionally used for arrays and collections to work with a similar syntax on observables. This is a great example of reactive programming because instead of deciding when to perform a data access (and having to check if it is possible and everything is in range and so on), the code would just wait for something to happen, for an event that provided data, then act on the data.

  One might argue that Verilog, a hardware description language, is also reactive, as it is based on actions being performed on certain events and it even uses non-blocking assignments, which are like declarations of state change which happen at the same time. Reminds me of the way React is implementing state management.

  Of course, reactive programming is also modern UI and when I say modern, I mean everything in the last twenty years. Code gets executed when elements in the user interface change state: on click, on change, on mouse move, on key press etc. That is why, the developers at Facebook argue, browser based UI programming should be reactive at the core. This is not new, it's something you might even be already very familiar with in other contexts. Code that is triggered by events is also called event-driven programming.

  But at the same time, others also claim their software is reactive. Microservices are now very fashionable. The concept revolves around organizing your product into completely independent modules that only have one external responsibility, which then one wires together via some sort of orchestrator. The biggest advantage of this is obviously separation of concerns, a classic divide and conquer strategy generalized over all software, but also the fact that you can independently test and deploy each microservice. You don't even have to shut down running ones or you can start multiple instances, perhaps with multiple versions and in different locations. This is also distributed programming. The way the communication between microservices is done is usually via some sort of message queue, like Rabbit MQ, but I am working on a really old software, written like 15 years ago, which uses IBM MQ to communicate between different portions of the software - let's call them macroservices :) Well, this is supposed to be reactive programming, too, because the microservices are reacting to the messages arriving on the queue and/or sent from others.

  The observer pattern is old, it's one of the patterns in the original design patterns book Design Patterns: Elements of Reusable Object-Oriented Software, which started the software design pattern craze which rages on even now. Anybody who ever used it extensively in their software can (and many do) claim that they did reactive programming. Then there is something called the actor model (which will probably confuse your Google if you search for it), which is actually a mathematical concept and originated in 1973! Implementations of actors are eerily similar to the microservices concept from above.

  And speaking of events, there is another pattern that is focusing on declaring the flow of changes from a given state, given an event. It's called a state machine. It also boasts separation of concerns because you only care about what happens in any state in case of an event. You can visualize all the possible flows in a state machine, too, as names arrows from any state to another, given that such a transition is defined. The implementation of the state machine engine is irrelevant as long as it enables these state transitions as defined by the developer. 

  Everything above, and probably some other concepts that are named differently but kind of mean the same thing, is reactive programming. Let me give you another example: a method or a software function. Can one say it is reactive? After all, it only executes code when you call it! Couldn't we say that the method reacts to an event that contains the parameters the method needs? What about Javascript, which is designed to be single threaded and where each piece of code is executed based on a queue of operations? Isn't it a reactive programming language using an event bus to determine which actions to perform?

  And that's the rub. The concept of reactivity is subjective and generally irrelevant. The only thing that changes and matters is the implementation of the event transport mechanism and the handling of state.

  In a traditional imperative program we take for granted that the execution of methods will be at the moment of the call and that all methods on that thread will be executed one after the other and that setting a value in memory is atomic and can be read immediately after by any other piece of code and you can even lock that value so it is only read by one entity at a time. Now imagine that you are writing the same program, only we can't make the assumptions above. Calling methods can result in their code getting executed at an arbitrary time or maybe not at all. Whatever you change in a method is only available to that method and there is no way for another method to read the values from another. The result? Your code will take a lot of care to maintain state locally and will start to look more like a state machine, modelling transitions rather than synchronous flows. The order of operations will also be ensured by consuming and emitting the right sort of events. Permanent and/or shared storage will become the responsibility of some of the modules and the idea of "setting data" will become awkward. Keeping these modules in sync will become the greatest hurdle.

  That's all it is! By eliminating assumptions about how your code is executed, the result is something more robust, more generic, more compartmentalized. Is it the golden hammer that will solve all problems? Of course it isn't. We've seen how the concepts at the core of reactive programming have been there since forever. If that was the best way, everybody would already be working like that. The biggest problems of this kind of thinking are resource duplication, as everybody has to keep all the data they use locally, and synchronization, as one cannot assume there exists any source of absolute truth that can be accessed by all at the same time. Debugging the system also becomes a bit complicated.

  In 2014 a bunch of people created something called "The Reactive Manifesto" and anyone can sign it. In it, they define a reactive system as:

  • Responsive - responds quickly
  • Resilient - remains responsive in case of failure
  • Elastic - remains responsive regardless of workload
  • Message Driven - async message passing as the boundary between components

  As you can see, reactive mostly means responsive for them and the concept is more one of organization management than a specific set of programming languages and tools. Note that, in fact, you can create a system that communicates via async message passing between components on the client, on the server, between client and server and so on. There can be multiple types of technology and different stacks. As long as they can react to asynchronous messages, they can be integrated into such a system. 

  This post has reached already a big size and I haven't even touched on functional programming and how it tries to solve... well, everything. I will do that in the next chapter. I have to say that I find the concept of a programming language that eliminates global variable scope and public fields and introduces a delay and a random order of execution of methods or properties from other classes fascinating. Imagine testing and debugging that, then moving the working code to production, where the delay is removed. You will also see that a lot of the ideas above influence how React development is done and perhaps you will understand purists telling everybody how things are not correct until you implement this or that in a certain way. Till next time!

Learning from React series:

  • Part 1 - why examining React is useful even if you won't end up using it
  • Part 2 (this one) - what Facebook wanted to do with React and how to get a grasp on it
  • Part 3 - what is Reactive Programming all about?
  • Part 4 - is React functional programming?
  • Part 5 - Typescript, for better and for worse
  • Part 6 - Single Page Applications are not where they wanted to be

In order to understand React we must consider what were the advantages that Facebook found in the concept when they created the library. There a numerous presentations and articles that they pushed to explain it, but it kind of distills to this:

  • mutation of values complicates flows in complex applications
  • traditional Model-View patterns promote mutation through two directional data binding
  • solution for mutation:
    • use unidirectional data binding and re-render views as the data changes
    • send inputs as events that a higher level entity will interpret
  • solution for slow browser render overhead:
    • code is organized in smaller and smaller components that depend on a few values in the overall data
    • there is an intermediate layer of rendering between React and the actual browser DOM called a Virtual DOM, which only sends to the browser the changes that renders affected

But wait, you will say! How do the values change if they are immutable? The point here is that your components have an immutable internal state. The values that are passed to the components can still change, but on a higher level. They declare a label that have a text and for the label the text never changes. When the text changes in the logic of the application, a new label instance with a new text is rendered. The advantage of this is that the declaration of the render for a component defines the way the component will always render. It's declarative of your intent of how that component should look. They wanted to replace mutation with what they called reconciliation between the previous state and the current state. They almost treated web development like game development or remote access software.

So when you look at a JSX syntax and you see Javascript mixed with HTML and switching back and forth, that is different from the ASPX spaghetti code where server logic was mixed up with UI declarations. JSX is less an XML flavor and more a Javascript flavor. In fact, it is transpiled to Javascript code when executed and the changes to the UI are imperative commands that tell it how to change based on how the render code affected the component. But for the developer it's just a story of how the component should look given some data.

React was released in May 2013 and it went through some transformations on the way. Internally it probably started as an object oriented approach which was cumbersome and fought with the overall design of Javascript. They fixed that by the time of the release by using the JSX syntax, but still with code looking like

var component = React.createClass({ render: function() { return <something/>; } });

And further down the line they came up with React hooks, which move further from the class oriented approach and more towards a functional one with stuff like

const component = (props) => (<something />);

which of course is lighter still. Note that Javascript changed during that time, allowing for more stuff to happen. And now they added Typescript support, so you get something like

const Component = (props:{text:string})=>(<something />);

This evolution of the library is also one of the biggest obstacles against learning how to use it as in your Goggle search you might find solutions and problems from any time in the history of the library. You will find the perfect tool for what you wanted, but all the examples are in Javascript and in Typescript it works differently or the answers refer to previous versions of absolutely everything and you don't know which of them is the one that should apply to your task. Or even worse, some package that you use and it made your life so easy conflicts with the one you just want to use because they were never meant to work together.

As opposed to Angular, which was designed as a framework, to constrain and control what you do, React is a library. And it evolves not only through the efforts of Facebook, but also of a very active community. People would add React to their existing project rather than rewriting it from scratch. This means they will have used any of the various versions of React as well as any of the various versions of all the packages that they use in conjunction with it. And these packages are wild! Imagine a developer coming from the world of WPF or vanilla web design with HTML and CSS as the primary focus and Javascript an after thought or from Angular. They will work with React, but use it in a way they are more familiar with. That means that even if the library has a backing philosophy, there is little it can do to force you to use it in that way.

Let's take just one example: MobX, a package that takes existing data objects and wraps them in proxies that notify of changes. With React you use it as you would a ViewModel in WPF. Instead of sending an event called CLICK from a click event and handling it in some state machine looking code you can just modify the "immutable" property of the data you were sent and behind the scene a setter is executed which lets everybody know that it has changed and so it triggers a re-render which will take the value of the actual property from the behind-the-scene getter. You get your way, React kind of gets its way.

To recap:

  • components live in a tree, rather than a graph, and they all render based on the properties they are passed
  • components declare how they should look like
  • any input from the components is sent up as an event to which the system "reacts"
  • slow browser rendering is replaced with a virtual representation of the UI and updated with specific commands to reflect only the changes from one state to the other
  • React is an evolving beast with many heads and finding your own way of doing things lies at the root of any successful development effort

While exploring development with this library, developers have found various tools and concepts useful to integrate. As we usually do, they started to generalize these attempts and come up with some new principles or get to the root of the underlying flow. I want to spend the next part of the series discussing some of these more general or architectural ideas and try to see what they are worth.

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A few years ago I wrote an article about using RealProxy to intercept methods and properties calls in order to log them. It was only for .NET Framework and suggested you inherit all intercepted classes from MarshalByRefObject. This one is a companion piece that shows how interception can be done in a more general way and without the need for MarshalByRefObject.

To do that I am going to give you two versions of the same class, one for .NET Framework and one for .NET Core which can be used like this:

//Initial code:
IInterface obj = new Implementation();

//Interceptor added:
IInterface obj = new Implementation();
var interceptor = new MyInterceptor<IInterface>();
obj = interceptor.Decorate(obj);

//Interceptor class (every method there is optional):
public class MyInterceptor<T> : ClassInterceptor<T>
{
    protected override void OnInvoked(MethodInfo methodInfo, object[] args, object result)
    {
        // do something when the method or property call ended succesfully
    }

    protected override void OnInvoking(MethodInfo methodInfo, object[] args)
    {
        // do something before the method or property call is invoked
    }

    protected override void OnException(MethodInfo methodInfo, object[] args, Exception exception)
    {
        // do something when a method or property call throws an exception
    }
}

This code would be the same for .NET Framework or Core. The difference is in the ClassInterceptor code and the only restriction is that your class has to implement an interface for the methods and properties intercepted.

Here is the .NET Framework code:

public abstract class ClassInterceptor<TInterface> : RealProxy
{
    private object _decorated;

    public ClassInterceptor()
        : base(typeof(TInterface))
    {
    }

    public TInterface Decorate<TImplementation>(TImplementation decorated)
        where TImplementation:TInterface
    {
        _decorated = decorated;
        return (TInterface)GetTransparentProxy();
    }

    public override IMessage Invoke(IMessage msg)
    {
        var methodCall = msg as IMethodCallMessage;
        var methodInfo = methodCall.MethodBase as MethodInfo;
        OnInvoking(methodInfo,methodCall.Args);
        object result;
        try
        {
            result = methodInfo.Invoke(_decorated, methodCall.InArgs);
        } catch(Exception ex)
        {
            OnException(methodInfo, methodCall.Args, ex);
            throw;
        }
        OnInvoked(methodInfo, methodCall.Args, result);
        return new ReturnMessage(result, null, 0, methodCall.LogicalCallContext, methodCall);
    }

    protected virtual void OnException(MethodInfo methodInfo, object[] args, Exception exception) { }
    protected virtual void OnInvoked(MethodInfo methodInfo, object[] args, object result) { }
    protected virtual void OnInvoking(MethodInfo methodInfo, object[] args) { }
}

In it, we use the power of RealProxy to create a transparent proxy. For Core we use DispatchProxy, which is the .NET Core replacement from Microsoft. Here is the code:

public abstract class ClassInterceptor<TInterface> : DispatchProxy
{
    private object _decorated;

    public ClassInterceptor() : base()
    {
    }

    public TInterface Decorate<TImplementation>(TImplementation decorated)
        where TImplementation : TInterface
    {
        var proxy = typeof(DispatchProxy)
                    .GetMethod("Create")
                    .MakeGenericMethod(typeof(TInterface),GetType())
                    .Invoke(null,Array.Empty<object>())
            as ClassInterceptor<TInterface>;

        proxy._decorated = decorated;

        return (TInterface)(object)proxy;
    }

    protected override object Invoke(MethodInfo targetMethod, object[] args)
    {
        OnInvoking(targetMethod,args);
        try
        {
            var result = targetMethod.Invoke(_decorated, args);
            OnInvoked(targetMethod, args,result);
            return result;
        }
        catch (TargetInvocationException exc)
        {
            OnException(targetMethod, args, exc);
            throw exc.InnerException;
        }
    }


    protected virtual void OnException(MethodInfo methodInfo, object[] args, Exception exception) { }
    protected virtual void OnInvoked(MethodInfo methodInfo, object[] args, object result) { }
    protected virtual void OnInvoking(MethodInfo methodInfo, object[] args) { }
}

DispatchProxy is a weird little class. Look how it generates an object which can be cast simultaneously to T or Class<T>!

There are many other things one can do to improve this class:

  • the base class could make the distinction between a method call and a property call. In the latter case the MethodInfo object will have IsSpecialName true and start with set_ or get_
  • for async/await scenarios and not only, the result of a method would be a Task<T> and if you want to log the result you should check for that, await the task, get the result, then log it. So this class could make this functionality available out of the box
  • support for Dependency Injection scenarios could also be added as the perfect place to use interception is when you register an interface-implementation pair. An extension method like container.RegisterSingletonWithLogging could be used instead of container.RegisterSingleton, by registering a factory which replaces the implementation with a logging proxy

I hope this helps!

P.S. Here is an article helping to migrate from RealProxy to DispatchProxy: Migrating RealProxy Usage to DispatchProxy

Definition

So, the task at hand is the subject of a common interview question: Implement an algorithm to get all valid (opened and closed) combinations of n pairs of parentheses. This means that for n=1 there is only one solution: "()". "((" or "))" are not valid, for 2 you will have "(())" and "()()" and so on. The question is trying to test how the interviewee handles recursion and what is commonly called backtracking. But as usual, there's more than one way to skin a cat, although for the life of me I can't see why you would want to do that.

The solutions here will be in C# and the expected result is an enumeration of strings containing open and closed parentheses. The code can be easily translated into other languages, including Javascript (ECMAScript 2015 introduced iterators and generator functions), but that's left to the reader. Let's begin.

Analysis

Before we solve any problem we need to analyse it and see what are the constraints and the expected results. In this case there are several observations that can be made:

  • the resulting strings will be of length n*2 (n pairs)
  • they will contain n '(' characters and n ')' characters
  • they cannot start with a ')' or end in a '('
  • in order to generate such a string, we can start with a smaller string to which we add '(' or ')'
  • we cannot add a ')' if there isn't at least one corresponding unclosed '(' 
  • if we add a '(' we need to have enough characters left to close the parenthesis, so the number of unclosed parentheses cannot exceed the characters left to fill
  • we could count the open and closed parentheses, but we only care about the number of unclosed ones, so instead of "closed" and "open" values, we can only use "open" to represent unclosed parentheses

Let's go for some variables and calculations:

  • n = number of pairs
  • open = number of unclosed parentheses in a string
  • open cannot be negative
  • one cannot add ')' if open = 0
  • one cannot add '(' if open >= n*2 - substring.length

Recursive solution

A simple implementation of these requirements can done with recursion:

public IEnumerable<string> GenerateRecursive(int n, string root = "", int open = 0)
{
    // substring is long enough, return it and exit
    if (root.Length == n * 2)
    {
        yield return root;
        yield break;
    }
    // if we can add '(' to existing substring, continue the process with the result
    if (open < n * 2 - root.Length)
    {
        // if only C# could just 'yield IteratorFunction()' this would look sleeker
        foreach (var s in GenerateRecursive(n, root + "(", open + 1))
        {
            yield return s;
        }
    }
    // if we can add ')' to existing substring, continue the process with the result
    if (open > 0)
    {
        foreach (var s in GenerateRecursive(n, root + ")", open - 1))
        {
            yield return s;
        }
    }
}

However, every time you see recursion you have to ask yourself: could n be large enough to cause a stack overflow? For example this fails for n=3000. The nice thing about this method, though, is that it can be limited to the number of items you want to see. For example var firstTen = GenerateRecursive(1000).Take(10) is very fast, as the generation is depth first and only computes the first ten values and exits.

So, can we replace the recursion with iteration?

Iterative solution

In order to do thing iteratively, we need to store the results of the previous step and use them in the current step. This means breadth first generation, which has its own problems. Let's see some code:

public IEnumerable<string> GenerateIteration(int n)
{
    // using named tuples to store the unclosed parentheses count with the substring
    var results = new List<(string Value,int Open)>() { ("",0) };
    for (int i = 0; i < n*2; i++)
    {
        // each step we compute the list of new strings from the list in the previous step
        var newResults = new List<(string Value, int Open)>();
        foreach (var (Value, Open) in results)
        {
            if (Open < n * 2 - Value.Length)
            {
                newResults.Add((Value + "(", Open + 1));
            }
            if (Open > 0)
            {
                newResults.Add((Value + ")", Open - 1));
            }
        }
        results = newResults;
    }
    return results.Select(r=>r.Value);
}

It's pretty sleek, but if you try something like var firstTen = GenerateRecursive(1000).Take(10) now it will take forever since all combinations of 1000 parentheses need to be computed and stored before taking the first 10! BTW, we can write this much nicer with LINQ, but be careful at the gotcha in the comment:

public IEnumerable<string> GenerateLinq(int n)
{
    // looks much nicer with LINQ
    IEnumerable<(string Value, int Open)> results = new[] { ("", 0) };
    for (var i = 0; i < n * 2; i++)
    {
        results =
            results
                .Where(r => r.Open < n * 2 - r.Value.Length)
                .Select(r => (Value: r.Value + "(", Open: r.Open + 1))
            .Concat(results
                .Where(r => r.Open > 0)
                .Select(r => (Value: r.Value + ")", Open: r.Open - 1))
            );  // but if you do not end this with a .ToList()
                // it will generate a huge expression that then will be evaluated at runtime! Oops!
    }
    return results.Select(r => r.Value);
}

But can't we do better? One is going to stack overflow, the other memory overflow and the last one kind of does both.

Incremental solution

They did say this requires an incremental solution, right? So why don't we take this literally? '(' and ')' are like 0 and 1, as ')' must always follow a '('. If you view a parenthesis string as a binary number, then all possible combinations can be encoded as numbers. This means that we could conceivably write a very fast function that would compute all possible combinations using bit operations, maybe even special processor instructions that count bits and so on. However, this would work only for n<=32 or 64 depending on the processor architecture and we don't want to get into that. But we can still use the concept!

If a string represents a fictional number, then you can start with the smallest one, increment it and check for validity. If you combine the incremental operation with the validity check you don't need to go through 2n operations to get the result. It doesn't use any memory except the current string and it is depth first generation. The best of both worlds! Let's see some code:

public IEnumerable<string> GenerateIncrement(int n)
{
    // the starting point is n open parentheses and n closing ones
    // we use the same array of characters to generate the strings we display
    var arr = (new string('(', n) + new string(')', n)).ToCharArray();
    // iteration will stop when incrementation reaches the "maximum" valid combination
    var success = true;
    while (success)
    {
        yield return new string(arr);
        success = Increment(arr, n);
    }
}

private bool Increment(char[] arr, int n)
{
    // we begin with a valid string, which means there are no unclosed parentheses
    var open = 0;
    // we start from the end of the string
    for (var i = arr.Length - 1; i >= 0; i--)
    {
        // ')' is equivalent to a 1. To "increment" this string we need to go to the previous position
        // incrementing 01 in binary results in 10
        if (arr[i] == ')')
        {
            open++;
            continue;
        }

        // '(' is equivalent to a 0. We will turn it into a ')' to increment it,
        // but only if there are unclosed parentheses to close
        open--;
        if (open == 0) continue;

        // we 'increment' the value
        arr[i] = ')';
        // now we need to reset the rest of the array
        var k = n - (open + i) / 2;
        // as many opening parenthesis as possible
        for (var j = i + 1; j < i + 1 + k; j++)
        {
            arr[j] = '(';
        }
        // the rest are closing parentheses
        for (var j = i + 1 + k; j < n * 2; j++)
        {
            arr[j] = ')';
        }
        return true;
    }
    // if we reached this point it means we got to a maximum
    return false;
}

Now doing GenerateIncrement(1000000).Take(10) took more to display the results than to actually compute them.

More solutions

As this is a classic interview question, there are a billion solutions to it at LeetCode. Yet the purpose of interview questions is to find out how one thinks, not what the solution of the problem actually is. I hope this helps.