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Nikola Stojaković
Nikola Stojaković

Posted on • Originally published at

Why our software is broken?

Long time no see! Since May when I wrote my last post, many things happened in my life. I started living alone, moved to a new city and found a new job. I think I had pretty good rest from the writing. Today, I’ll write about a topic which interests us all; C-level staff, developers, managers, end users… Recently, I watched an amazing talk by Joe Armstrong in which he presented quite interesting and a bit controversial thought;

Computer science is confusing because it’s not a science and there are too many ideas floating around.

I sincerely believe this can explain lot of issues in software development currently. We’re constantly trying to improve quality of our software, lower the time it takes to build it and prevent bugs. When confronted with the question how to build a quality software, different people will give you different answers. Some hardcore FP enthusiasts will try to persuade you to rewrite whole your back-end in Haskell. That person in the corner will swear by TDD. A manager on the third floor will say we should ditch agile and use waterfall.

Most people are missing a huge factor here; a failure to reduce complexity.

Personal experience

In the company I worked in the past, we received a new project which had to be done in React. At that time I had a bit of experience with React and understood basic ideas behind it. There was another colleague on that project who almost never worked with React before. Right at the start, we received a task to create an image configurator. On the surface, it was basic; you could choose colors, icons, text font and other stuff. What made it quite complex was a bad design. Instead of using states, my colleague (understandably, since he worked mostly with jQuery before) did direct mutations on the DOM. If you worked with React seriously, you know this is a big no-no.

Unfortunately, this part grew and became harder and harder to maintain, to the point where we spent half an hour fixing some trivial issue. This was the first time in my career where I saw how important it is to try to reduce complexity as much as you can. Sometimes we tend to go too far when we’re solving particular problem. Always keep in mind that you’re writing for other people first, and then for the machine. Machine won’t maintain your code; you’re the one who will have to explain it to others. Even if you leave the company before that, don’t do something you won’t like to experience yourself.

Alright, but how can I reduce complexity?

Now, there is a catch. Unfortunately, it’s possible to reduce complexity of your code only to some degree. Software is inherently complex on it’s own. It has to take inputs, handle edge cases and errors, work with files and data received over the network, draw things on the screen and many other stuff. We’re developing on the machines which are dozens of times more powerful than the ones used fifty years ago. On top of that, you have deadlines, poorly documented libraries, legacy code etc. It’s understandable why software development today is much more challenging in many ways.

  • Don’t try to appear smart. If there is a simple way to solve particular problem which works and is easy to understand, use it. Don’t build unnecessary abstractions and features no one asked for. Use descriptive variable and method names. It’s much smarter to write code which is easy to understand and maintain than something which only you will understand.
  • Write documentation. Even you won’t be able to understand some parts of your code after some period of time. Describing what some part of your code does will help other people working on your code and it will help you later as well.
  • Write tests. Sometimes, writing a test before you start implementing certain feature will help you to better design it.
  • Ask yourself do you really need it. I can’t find that article now, but I think it was written by Joel Spolsky, ex-CEO of StackOverflow. I use it as my guiding star and I think about it whenever I’m starting to work on a new side project. In essence, it says this; your job is not to write the code, but to solve problems. Ideally, you should solve them without writing any code. Most of the time it’s not possible though, so you should strive to write least possible amount of it which will be both, well working and understandable.

There are many other ways but these are some of the most important ones. Remember, it’s always about balancing. Adding new features will definitely make a whole system more complex, but that doesn’t mean we shouldn’t add new features at all. It means we should be more careful when doing so, taking into account the most important things; value it gives us (both in the short-term and long-term) as well as the effort it takes to be built and maintained.

Things should be as simple as they can be, but not simpler than that

I’m using this Einstein’s quote fairly often when I’m talking about software development. It’s so amazing because it can be applied across many different fields. Reducing complexity in the project shouldn’t mean oversimplifying stuff. As I said, software is inherently complex on it’s own; trying to simplify something too much will have the opposite effect. For example, if you’re building a web application similar to Lichess, you’ll have to think about lots of things:

  • fault tolerance
  • handling hundreds of thousands of concurrent users
  • streaming
  • security

And so on and so on. As long as you can have controlled complexity in the project, it’s okay for it to exist in the project. Controlling complexity means building a flow which will help new developers to learn how the system works so they can make contributions to it. Most obvious tool for that job is writing documentation. In an article The Plea for Lean Software written by Niklaus Wirth, creator of Pascal, he says something which was proven to be true more than two decades later:

The belief that complex systems require armies of designers and programmers is wrong. A system that is not understood in its entirety, or at least to a significant degree of detail by a single individual, should probably not be built.

To sum up; it’s okay for some things to be complex. What you should prevent though is for things to become so complex that adding each new feature will take significant amount of time. This will make maintenance of the software painful and lead to even higher complexity in the future. The initial effort of implementing a feature is not as important as the effort of maintaining it.


I intentionally made this article smaller than I planned to. My goal was to motivate you to think about this more. We’re witnessing enormous expansion of the software and I believe this topic will be even more relevant in the future. I’ll leave you to think more about this on your own and to do your own research on this problem. Before that, I’ll recommend you an amazing book I recently read; Code Simplicity: The Fundamentals of Software by Max Kanat. It’s only 80 pages long but contains lot of valuable information on reducing software complexity and overall proper software design. I’ll suggest you to read it and take notes. No matter which technology you use or how your projects will look, these points will be helpful to you for the rest of your career.

Top comments (1)

joelbonetr profile image
JoelBonetR 🥇 • Edited

I want to focus on that because it's the root of the problem:

Computer science is confusing because it’s not a science and there are too many ideas floating around.

I can disagree with that adding some arguments.
Computer science is, as it's name says, a science. This can be easily proved by the fact that it can be peer reviewed and you can get exact results.

If I state that a given algorithm or function has a complexity of O(n^2) it will be the same on any try to reproduce this.

The ideas floating around can be studied using different approaches such i.e. logic or mathematics.

What is not a science is the application of the computer science.

If we have in mind software development, many roles intervene in that, such software engineers, technical engineers, technical devs or even self-taught individuals that probably never learned a good base (because when you learn something by your own you usually learn what you like most and ditch the rest) to understand what's going on when they state something inside a runtime environment.

with this team, you'll have to handle different ways to "think" (we'll come later on the reason for the quotation marks on think). Let's order the things from bottom to top:

  1. An average self-taught or a bad [insert one of the following here] would say they need to use what they already know how to use.
  2. A good software technician would say that they need to break down problems to find out the needs and thus the correct tech stack, architecture, design and so on.
  3. A good technical engineer would say that they need to analyse the overall and break down problems to find out the needs and thus the correct tech stack, architecture, design and so on.
  4. A good engineer would say that they need to break down problems into small pieces and analyse them to find out the needs and thus the correct tech stack, architecture, design and so on.

You can extend this using any role and what they are intended to solve inside the team. But due to this fragmentation opinions appear. On science there are not opinions, there are possible statements that can (or not, depending on the current situation of the tech evolution) be proven and evaluated as true or false, then be peer reviewed and get a strong closed statement (it is like that, it is not like that) or a question as answer (it's sometimes like that but we need to know the reason for "sometimes").

Then the quotes on "think". There's a difference between thinking something (having an opinion) and knowing something.
I know that 2+2 equals 4 and I think that the sky is blue. Maybe it's from another colour and it's the effect of the sunlight passing some molecules that makes me see that blue sky but in fact it's not, I don't know, so I just have an opinion, I "think".

We are currently living on an era that people opinions seem to matter. I mean that nobody currently cares about what you think like always has been but with social media... people join other individuals with similar ideas and they think they are a big group, superior to the rest of mortals that have some absolute truth.

This shitty behaviour is spread to any living human that is on the modern world like an hurricane. And we us, working on IT are not different or isolated from this phenomenon.

*** a new lib appears and if (and only if) it takes some prominence, automatically haters and prophets of this new tech appear.
None of them polarised set of people had it's time deep understanding this new tech or ensuring it really solve what it came to solve.

Of course human behaviour is a different science but it's just that even being a science, not all people involved are scientific so they don't assume and test statements, they fight to try to seem right at other's eyes and opinions instead being right or wrong by knowing.

Now imagine a doctor being self taught, without any college certificate that warranty that he/she had acquired a minimum knowledge. Or with an official non-university certificate that certificates a little scope of the entire medical science.
Which tasks do you let this doctor do? Surgery? I don't think so. Dermatology? hmm probably not.

Why do we listen to people who have not even made an effort to understand the things they think about?

Wee need a collegiate number to post things on a serious place and make an effort to explain on a more plain way those concepts into platforms like this. Because the people will not stop this behaviour but it does not mean that this behaviour must be spread and contaminate each IT forum or place where to get information.

StackOverflow tried this but as it's free for anyone your post can be down-voted for any reason or opinion even without requiring other users to read so... it was a bad idea that leads to a toxic behaviour.

*Sorry for the bible