The other day I was reviewing my colleagues’ code. It was back-end code written in C#. I noticed that he introduced a class that is very similar to the structure I was quite sure existing in the .NET base library. I found that structure in Microsoft documentation and we agreed that it is better to use .NET type instead of introducing the same type with a different name. After that occasion, I recalled several other cases when I saw the unique solutions for the problems that could have been solved by well-known pattern or practice. My gut feeling was telling me then that it is not a good idea to introduce your own solution for a problem that is already solved by someone else, but I have never really thought what problems such decision can introduce in the project. And so in this article, I wanted to share some thoughts regarding the widely accepted and unique solutions in software development.

First let’s make it clear that any best practice, framework, algorithm or technology was a unique solution in their time. Then when exactly one or another solution became widely accepted?

• There are solutions in computer sciences that can be measured, like algorithms. In order to estimate the cost of algorithm calculation Big O notation was introduced. When someone comes up with a new algorithm for common problem, for example sorting, we can simply compare how fast each algorithm solves the problem using big O, and choose the one that meets our criteria. And if the new algorithm beats the old one in performance working on the same data, then it becomes the new standard.
• But most of the technologies, frameworks, patterns and best practices can not be compared by introducing measurable parameters. Think about programming languages or frameworks. There is noway you can make an unambiguous claim which language or framework is better. Then how to find out what is the best language or framework for the given problem. Let me share a story from my youth that might give some insight how the new solution become widely accepted. I remember the story that was shared by my Assembler class professor at University. He started his computer scientists career when software was written in punch cards and he became very good at writing machine code and later at Assembler. And when the first compilers emerged such as FORTRAN and ALGOL he was very skeptical regarding these new languages and the compiling technology in general, because he didn’t believe that the compilers algorithm is able to produce the same quality machine code as a skilled Assembler developer. And in the fifties and sixties well written assembly code really metered, because every byte was counted and his reasoning at that time was valid. But time passed by the hardware and compilers improved and we see that most of the code even in embedded systems now days is written in high level programming languages. The same story goes for programming paradigms – the business application world started with procedural programming and today it ended with Object oriented programming. In Windows and Mobile apps we started with Forms and Activities and today ended with MVVM. So it looks like for such things as programming languages and frameworks more or less useful criteria that we can use is
  • the amount of time the technology is used,
  • amount of software written using the the particular technology
  • number of developers actively using the particular technology

And still all these criteria are not so reliable as big O for algorithms.

In case of algorithm I think it is quite clear that if there is already an algorithm that solves the problem it is pointless to write your own, unless you can produce better one. In case of frameworks I would follow the same logic – if there is an well known framework that can solve the problem it is much safer to relay on the majorities opinion (although the majority can be wrong) rather than on your own single point of view. Even if the framework or pattern will be rejected in the near future at this moment:

• it is much more tested than your own solution, and therefore there are much more chances to have a flaw or even bug in your solution than in the widely accepted solution
• it will be much easier for other developers to work with widely accepted solution than yours, because there is much more documentation and all kind of sorts information about the widely accepted solution than you can ever produce. And this will become crucial when your solution will start to live it’s own live

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In my last article I mentioned that we had cases when we needed to split our back-end application across several processes and as a result we gained more flexibility when we needed to scale the application. This time I want to keep sharing some insights on why we try to keep some parts of the application loosely coupled. This time I wanted to talk about loose coupling at design time when the whole application might run in the single process. According to one of the definitions ”loosely coupled system is one in which each of its components has, or makes use of, little or no knowledge of the definitions of other separate components”. In object oriented paradigm, that we are using to create our Fitradar application, most of the code is spread among various classes and therefore the smallest component that we consider is a class. And since classes are just containers for data and functions then we usually see the loose coupling as a way how to call a function of another class with little information as possible.

The simplest way how to call a method on the other object is to create that object from a class (in Java and C# we do that by new operator) and call the needed method. But it turns out there are many cases when it is undesirable to know the class name of an object or even a specific method name during the design time and therefore there are several methods how to reduce the knowledge of a class we are going to use and a method we are going to call:

• We can replace a class with an interface or an abstract class and in such way reduce the information about the class to the subset of methods that the other classes are interested in. In Object Oriented programming this is known as Polymorphism and is one of the OOP cornerstones. It is really hard to express how important this OOP feature is. I think back in a day that feature was one of the selling points of OOP that pushed out the procedural programming. The biggest gain of using Polymorphism is a flexibility. Now we are not bound to a single code execution flow, because every function that is presented in the execution flow via interface or abstract class can be replaced with other implementation through the configuration or dynamically during a runtime. This in turn opens whole bunch of new possibilities. And the one I like the most is Unit testing. Now days it is hard to imagine how much work it would require to isolate the piece of code and test it without the interfaces that can be mocked.
• Sometimes we are interested only in one method of the other class and we don’t want to be bound to single class that implements this method, and we want to replace that method implementation. In order to reduce the knowledge about the other class to single methods signature we can use delegates in C#, functional interfaces in Java, Kotlin or function pointers in C\C++. Not all OOP languages provide such constructs though then we should use more verbose interfaces or abstract classes. A delegate can bee seen as placeholder for a method. And once we start to focus on a method without accompanying class we start to enter the realm of Functional programming where function implementation can be written as lambda expression (anonymous functions) and its return type and arguments can be other functions. The most common areas where the function placeholders are used are events and callbacks. And once Linq came out everyone who got to know this library really started to appreciate lambda expressions
• In cases where Interfaces and Anonymous methods are not enough to describe dependency, for example we don’t want to restrict a method description in our execution flow with a single signature and want to use different rules to describe the method or a class that contains the method, then we can use Reflection. Although Reflection is very powerful tool that allows to achieve a great flexibility, usually it is not recommended to use because it adds an overhead at runtime and degrades the performance

On the larger scale where components are not anymore single classes but the whole systems the loose coupling further can be achieved by introducing the middle-ware like Queues and Service Buses.

As we can see making a method call something that is not bound to a single implementation opens up a dozen of options how to design and build an application in very flexible way.

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