Increase Local Reasoning with Stateless Architecture and Value Types

It is just another Thursday of adding features to your mobile app.

You have blasted through your task list by extending the current underlying object model + data retrieval code.

Your front-end native views are all coming together. The navigation between views and specific data loading is all good.

Git Commit. Git Push. The build pops out on HockeyApp. The Friday sprint review goes well. During the sprint review the product manager points out that full CRUD (Create, Read, Update, Delete) functionality is required in each of the added views. You only have the ‘R’ in ‘CRUD’ implemented. You look through your views, think it just can’t be that bad to add C, U and D, and commit to adding full CRUD to all the views by next Friday’s sprint review.

The weekend passes by, you come in on Monday and start going through all your views to add full CRUD. You update your first view with full CRUD; start navigating through your app; do some creates, updates, and deletes; and notice that all of those other views you added last week are just broken. Whole swaths of classes are sharing data you didn’t know was shared between them. Mutation to data in one view has unknown effects on the other views due to the shared references to data classes from your back-end object model.

Your commitment to having this all done by Friday is looking like a pipe-dream.

Without realizing it you are now a victim of code that is not locally reasoned due to heavy use of reference types.

Local reasoning is the ability of a programmer to look at a single unit of code (i.e. class, struct, function, series of functions) and ensure that changes made to data structures and variables within that unit of code don’t have an unintended effect on unrelated areas of the software.

The primary example of poor local reasoning is handing out pointers to single references of classes to many different areas of the application. These pointers to single references are then mutated by all the clients that were handed the reference to the shared instance.

Adding to the pain is the possibility that a reference to your single instance was held by a client, then mutated by a parallel running thread.

Code that you thought that was one-pass, single-path, easy-peasy has now become a spider web of live wires blowing in the wind that short circuit and spark at random times.

With the recent rise of Swift, there has been a movement to use value types to avoid all that sparking caused by random mutation within reference types.

For so long, we were conditioned to use classes types for everything. Classes seem like the ultimate solution. Lightweight hand off of references (i.e. pointers), instead of allocation and copying of all internal members across function calls. The ability to globally mutate in one shot via known publicly exposed functions. It all looks so awesomely ‘object-oriented’. Until you hit the complex scenarios that a CRUD based user interface has to implement. Suddenly that awesome class based object model is being referenced by view after view after subview after sub-subview. Mutation can now occur across 10s of classes with 10s of running threads.

Time to go way too far up the geek scale to talk about possible solutions.

A classic trope in many Star Trek episodes was something sneaking onto the ship. Once on the ship, the alien / particle / nanite / Lwaxana Troi would start to wreak havoc with the red shirts / warp core / main computer / Captain Picard’s patience (respectively).

By using nothing but classes and reference types, even with a well defined pure OO interface to each, you are still spending too much time with your shields down, and letting too many things sneak onto the ship. It is time to raise the shields forever by using value types as an isolated shuttlecraft to move values securely between the ship and interested parties.

Apple has been emphasizing the use of value types for the past two years via their release of the Swift language.

Check out these WWDC 2015 /2016 presentations which emphasize the use of Swift value types as a bringer of stability and performance via using the language itself to bring local reasoning to code:

Apple has even migrated many existing framework classes (i.e. reference typed) to value types in the latest evolution of Swift 3.0. Check out the WWDC 2016 Video: What’s New in Foundation for Swift.

At Minnebar 11, Adam May and Sam Kirchmeier presented on Exploring Stateless UIs in Swift. In their presentation, they outline a series of techniques using Swift to eliminate common iOS state and reference bugs. Their techniques meld together stateless concepts from React, Flux, and language techniques in Swift, to dramatically increase the local reasoning in standard iOS code.

Riffing off of Adam and Sam’s presentation, I came up with a basic representation of stateless concepts in Xamarin to solve a series of cross-platform concerns.

The rise of using value types as a bringer of local reasoning to code is not just isolated to Apple and Swift. The recognition that emphasizing local reasoning can eliminate whole swaths of bugs is also burning it’s way through the JavaScript community as well. React.js and underlying Flux architectural concepts enforce a one-way-one-time push + render to a view via action, dispatcher, and store constructs. React + Flux ensure that JavaScript code doesn’t do cross-application mutation in random and unregulated ways. The local reasoning is in React + Flux is assured by the underlying architecture.

Even the PUT, DELETE, POST, and GET operations lying underneath REST based web interfaces are recognition of the power of local reasoning and the scourge of mutation of shared references to objects.

C# and .NET languages are very weak on the use of value types as a bringer of local reasoning. For so long Microsoft has provided guidance along the lines of ‘In all other cases, you should define your types as classes‘, largely due to performance implications.

Have no fear, you can bring similar concepts to C# code as well via the struct.

The one draw back of C# is the ease with which the struct can expose mutators in non-obvious ways via functions and public property setters.

Contrasting with C#, Swift has the ‘mutating‘ keyword. Any function that will mutate a member of a struct requires the ‘mutating‘ keyword to be attached in order for compilation to succeed. Unfortunately, there is no such compiler enforced mutability guard for structs in C#. The best you can usually do is to omit the property set from most of your struct property definitions, and also use private / internal modifiers to ensure the reasoning scope of your type is as local as you can possibly make it.

The next time you see a bug caused by a seemingly random chunk of data mutating, give a thought to how you may be able to refactor that code using stateless architecture concepts and value types to increase the local reasoning of all associated code. Who knows, you may find and fix many bugs you didn’t even realize that you had.

C# vs. Swift – Iron Man vs. Captain America

In Captain America: Civil War we get to see the ultimate battle between Iron Man and Captain America.

It is a battle of simple gutty defense vs. smart weapons and flashy offense, humility vs. brashness, down in the dirt vs. up in the clouds.

To totally geek it up, the same kind of battle exists in the languages that software engineers use today and I believe this is especially true in the battle of C# vs. Swift.

Don’t worry, this really isn’t a versus type write up. If anything I seek to point out each language’s unique strengths, then show how software engineers can get into the right superhero mindset to really use those strengths, and be aware of the weaknesses, to create great solutions.


C# = Iron Man – Strong Flashy Offense

C# is truly the Iron Man in this comparison. It is amazing how much showy weaponry C# can bring to bear to solve problems.

  • Have a problem with your UI freezing up? Bring in Task<T> / async – await, and seamlessly refactor years old code to be fully asynchronous, even within native UIs where thread synchronization is key.
  • Have a super large dataset that you need to tame? Bring in IEnumerable<T> / yield return or Lazy<T> from the deferred execution realm.
  • Have a need to produce arrays and collections that are the result of super smart functional filtering? Bring in LINQ.
  • Need to do smart filtering of XML? Bring XDocument and its magic LINQ over XML powers.
  • Need to do JSON processing? Head on over to NuGet, reference Newtonsoft.JSON ,and get stable, powerful JSON serialize / deserialize behavior and be done in no time.
  • Need to hit a REST service with super specific HTTP header formatting and authentication? System.Net.Http has you covered.
  • Need a cross-platform way to retrieve data from remote sites + Model / View / View Model architecture? Check out ReactiveUI.
  • Need async but inline immediate responses to collection changes? Check out Rx.NET.
  • C# is strongly typed, but you can also use reflection and loosen that strong typing as needed.
  • C# can even be used to generate itself.

You can even do most the above across all platforms. Windows, Windows Mobile, Android, iOS, Linux servers, … C# has you covered, in any way, any time, any where.

There is every gadget and gizmo that you can bring in and bolt on to existing C# code to get your job done. Even the very oldest C# code from 2002 is still supported and easily transformed using Visual Studio, or Resharper tooling into something shiny and modern.

C# has all these weapons, but the lifetime of these weapons are sometimes mere seconds before they are replaced with the next version via NuGet. The masters of C#, just like Tony Stark, have no issue with throwing out just created stuff in favor of the next great thing.

C#’s weaknesses are the dreaded NullReferenceException and the indeterminate mutability of most data structures. C# is great at attacking problems, and hitting at the 90% of the solution in a lightning quick way. However, C# doesn’t play defense very well. If you go too fast too far with C# you can out run your air cover, leaving you vulnerable when attacked from the flanks by null members, timeout errors, weird data changes, unhandled exceptions, or not connected to network scenarios.

C# is a highly flexible, multi-weapon language that you can use to attack any problem.

Swift = Captain America – Strong Defense

Swift is the ultimate boots-on-the-ground and in-the-mud defensive language. In Swift you don’t solve problems by attacking them head on with whole armories of shiny weaponry, you hunker down, put your shield up, and start slogging up that hill one step at a time.

Every line of Swift code written requires the author to think of the worst case:

The inventors of Swift must have looked at the metrics of existing Objective-C iOS applications and realized that the number 1 and 2 problems were:

  • Coders not realizing that the data they are changing on one screen leads to changes in data on other screens.
  • App crashes due to trying to access the value behind a null pointer.

Defense was needed. The power of Captain America’s vibranium shield was needed, only this time wielded by coders to stop these major in-app issues.

Coding in Swift is highly defensive in nature. To see this in action take a look at Swift Optionalsif .. let syntax, and the class initialization rules. As you use them, Swift optionals will permeate your entire thinking as you rev up your data structures. Every variable you use and/or create needs to be immediately thought of in terms of optional vs. non-optional.

Within Swift the use of specific reference and value types allows you to defend against unwanted mutation to your data structures.

Each line of defensive code is one more brick piled on top of other bricks of defensive code. When done you end up with applications that resemble the Great Wall of China and are truly written for the worst case. This layered defensive code coordination leads to super solid software structure that can take a real beating when attacked by the invaders (or users) of the software.

When done solving the problem in Swift you have a beautiful shiny shield that can repulse almost any mutability or null data attack. Because you play so much defense in Swift, coding up solutions to things seems to take longer. In reality, you have taken all that defense that C# out ran and have incorporated it into the structure of the solution.

The constant nullability slog, coupled with the constant mutability slog, while coding in Swift leads the developer to wanting more weapons to go at problems. Constant defensive coding slog can lead to developer fatigue quite quickly. However, when the problem solution is achieved, the engineer can see that their defensive coding effort has been like using Captain America’s shield as their primary weapon.

With the future potential of Swift existing across platforms, it could mean more solidly crafted software across the board, from server side to mobile applications. The underlying thought process behind Swift is already starting to leak into other languages, especially in the area of nullability.

I know that Swift isn’t without its share of flashy bolt-on weapon systems. Comparing C# to Swift when it comes to third-party library support is like comparing Iron Man’s crazy spin laser and hand repulsors to any weapon Captain America has ever wielded (at least in the movies).


But who wins in the ultimate battle?

If you ask me, I think Captain America and Iron Man are both good guys who should be augmenting each other’s strengths and covering their corresponding weaknesses.  I bet the  *SPOILER* real big bad *SPOILER*  is hiding behind the scenes and making them battle it out.

As with all things in software engineering there is never a clear winner. There are drawbacks and advantages to the structure, approach, and capabilities of all languages and constructs. These drawbacks and advantages tend to fit or not fit for solutions to given problems.

Good ideas tend to bubble to the top (i.e. delayed execution, in-language async, nullability enforcement, mutability enforcement), whereas bad ideas tend to settle to the bottom (i.e. garbage collection in Objective-C).

Swift is so new, the in-language concepts so hardened, the community so outspoken and willing to move quickly, that the verdict is not yet out.

C# has been around so long, has so much weaponry, and is currently so incredibly flexible across even dynamic and functional concepts. There is no way C# doesn’t continue to flex with some of the core concepts surfacing from the Swift and Kotlin worlds.

Who knows, one day you just might see Iron Man wielding Captain America’s shield. Just like C# currently wields dynamic and functional constructs, C# could well start to take on deep nullability constructs as they exist in Swift.

At the end of the day, we all win as these 2 languages battle, take on, and wield the best parts of each other to surface great solutions to real software problems.

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The Disruptor is, essentially, a scheduling strategy builder for multithreaded code. It stands out in the world of concurrent programming because it offers both great execution speed and easily readable and debuggable code. Yes, it does have a weird name. According to the original whitepaper, it was coined “Disruptor” because

it had elements of similarity for dealing with graphs of dependencies to the concept of “Phasers” in Java 7…

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The Managed Extensibility Framework (MEF) from Microsoft is a framework that allows developers to create a plug-in based application that allows for designing extensible programs by either the developer or third parties.  The definition from MSDN is as follows (link):

It allows application developers to discover and use extensions with no configuration required. It also lets extension developers easily encapsulate code and avoid fragile hard dependencies. MEF not only allows extensions to be reused within applications, but across applications as well.

At first glance, it looks like just another IoC container, and it certainly can be used for dependency injection much the same as Ninject or other DI frameworks. But the true power comes when you realize that your dependencies can come from anywhere and be loaded and run at any time, and that is the true purpose of MEF. It allows you to create libraries or pieces of functionality in isolation that perform a very specific functionality (as well as unit test them isolation as well), and then plug them in to a much larger application. This gives you very clean separation of concerns in your code, and allows developers to focus on smaller projects simultaneously and deliver a final product to the client that much faster.

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Fast forward to 2013: most of your customers are now used to rich web applications like Gmail or Facebook. Furthermore it is likely they aren’t using the web as much in a browser but but are instead using thick client applications on their smartphone or tablet. Regardless of the the platform, one thing is certainly true: your customers aren’t asking for a rich experience in their applications, they are demanding it.

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Having a suite of automated tests for your code helps improve software quality and maintainability in several dimensions. Writing unit tests for your software is likely to cause you to incorporate several design aspects that make it easier for other developers to use your and which have the side-effect of dramatically increasing the maintainability of your code overall. Testable code typically has fewer tight couplings between components, dependencies that are injectable, and encourages SOLID design principles in a naturalistic way because SOLID code makes writing tests (and therefor all usage) of your code easier. Automated unit tests also help you write a verifiable usage contract between your components that enables you to find and isolate bugs or perform major refactoring on your code without fear of breaking existing features. All of this leads to higher quality software.
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