Tag Archives: programming

Code Writing from a UX Perspective

We often talk and discuss coding style and guidelines. Some of these discussions grow to be (some would say useless) flame wars, while others invoke thoughts and sometimes even reach a consensus, e.g. “GOTO considered harmful” (PDF). These discussions tend to be motivated by good intentions – making software development better; delivering software faster, with better quality and precision.

One area that keeps coming up is the need to have code written clearly; to make code easily understandable and changeable. It is generally agreed that code readability is important. And yet, the discussions are sometimes endless. We don’t seem to be able to agree what constitutes code that is written well enough, one that is easily understood. Claims made are often seen as very subjective and “a matter of taste”, as readability and code quality deals with human interpretation and judgement of said code.

At the same time, another field that deals with human-computer interaction seems to achieve better success in establishing at least some level of standard or agreed understanding of quality – software user experience (UX). Naturally, taste also plays a role in this case, but practitioners seem to agree more on some underlying practical principles to follow; similar to how coders have established some common understanding of good code design.

Which then begs the question – what if we approach code writing as a user experience problem, where the users are coders (incl. the code writer)?

Designers of applications’ user experience often deal with how the application is to be used. Characterizing its users and their main use cases. The answers to most of these questions are already known to us in the case of coders – we are the users. We write code, read it, test it, debug it. We know how we navigate code, skim through it, or how we approach refactorings.

Given that profiling the users is mostly out of the way, can we use this knowledge by taking a page from the UX designers’ playbook and applying it to code writing?
Can we design the code itself in such a way that will make our experience with it more productive and enjoyable, or dare I say delightful?

A naive approach would be to look at UI patterns and trying to apply them to code. While some may be somewhat useful (e.g. “inline hints”), it appears that the context of graphical UI design and its associated patterns does not immediately map to textual code writing. So while some insights can be had, this kind of mapping doesn’t seem to offer great value.

UX Principles in Code

But what if we go deeper?
Can we apply established principles of software-human interaction to code writing?

Take for example clarity. Good user interface designs are clear – at any point in the application they provide the user with an immediate understanding of what just happened, where is the user, what are the options available and their implications and so on. Think breadcrumbs, messages displayed, contextual disabling/enabling of buttons and so on.
What does this mean to code? Saying that “the code needs to be clear” is stating the obvious. Thinking about it from a user (=programmer) experience point of view we should be paying attention to the exact same things:

  • Is it clear to the user where he is from looking at the code?
  • Is the code conducive to understanding the options available at any given point?
  • Are implications of changes communicated clearly?

For example, consider a long file containing a lot of functionality, however related, a file with a lot of definitions, a class with a lot of methods and internal classes, nested callbacks, etc. These are examples of code that does not lend itself immediately to the structure and location in the code. It is harder to follow when reading and especially when debugging it; as debugging often involves jumping from file to file.
Similarly, having too many options to do one thing, e.g. overloaded functions, might introduce some confusion on what is the best way to do things. So there’s a clear tradeoff here between convenience (having the same method name, but with different parameters), and creating a confusing API.

Instead, keeping code listings shorter, tying code artifacts more closely to their location in the code base – e.g. one or two type(s) per file, can help with guiding the user of the code to understand what is the piece of code he is looking at. On the same note, providing one or two ways to do something, e.g. reading from a file or from stream, could actually make it easier for the caller of an API to understand what’s expected and how to work with that API.

Another principle to think about is familiarity and consistency. User interfaces, especially graphical ones, tend to prefer conventional solutions (hence patterns) for common tasks. Icons, links, color coding (red vs. green) are all examples of reusing familiar visual cues to convey meaning and being useful.

Familiarity can apply also to code writing. We can think of several places where this principle is applied:

  • Using common verbs, e.g. names of well known code design patterns
  • Naming getters and setters
  • Consistent naming for classes with similar roles
  • Well used parameter names – i for index, callback for callback functions, onXXX for event handlers
  • Packages following a similar scheme

Using well known patterns for organizing code, naming artifacts, etc. gives the programmer a better chance of understanding and navigating the code. At the project level it might make refactoring easier as it already suggests some code/module structure that can be followed, and may lead to more thoughtfulness with changes that break these familiar patterns.

Efficiency, of course, is also something to look into. Good user interfaces often emphasize the main scenarios supported by making them very efficient for the user. We count clicks, measure how much scrolling is needed, carefully design menus, etc. only to make sure that the common usage scenarios are easy to follow and accessible. In code this may translate to looking at the prevalent scenarios when coding. Readability is of course important, since we mostly read code. But another thing to consider is, for example, debugging and monitoring the running code. Do we insist, for example, on writing one operation per line, with variables defined for intermediate values; or do we cram together several access function calls making it harder to debug and trace the code?

Discouraging Bad Practices with Programmer’s User Experience

Another angle to look into the programmer’s user experience is to try and come with ways where the user experience actually encourages us to write better code.

An example for this is fibonacci indentation where each level of text indentation in the code is indented by a number of spaces matching the fibonacci number at that level. So deeper nesting levels are indented further away. At first, this may seem weird, but when you consider this, you quickly see how this discourages too much nesting – thus improving code readability and the overall experience when dealing with the code.

Another example might be to mandate no empty lines between a variable declaration and where the variable is used. This encourages declaring variables closer to where they are used, keeping related expressions closer visually; otherwise you end up with a big block of code – making it harder to follow.

How is this Useful?

These examples, and some of the conclusions presented here are nothing new to anyone considering the readability and clarity of code. Proper naming, for example, has always been in focus when considering code quality and readability. Still, it might be useful to frame the code readability/usability question as a user experience question, and borrow some practices from the field of user experience design. It helps to reason about better practices for structuring code.

Practically, this could be part of our code reviews, and configured/programmed into our already established set of coding tools – IDEs, linters, static code analysis tools, style guides, etc. The amount of tools available and polyglot nature of today’s software systems, where it’s not uncommon for a system to be coded in several languages, may in fact highlight the value of having a set of overarching principles and insights to guide us to better code writing. We should be able to define and follow principles that can be applied consistently and successfully in several languages at the same time.

One might argue, and justifiably so, that the job of making a programmer’s life easier is handled pretty well with the plethora of tools available, namely modern IDEs. But code can be made better (=easier to work with) by not relying on such mechanisms alone. Besides, not all editors are created equal, and code is viewed in tools other than the original IDE used to write it; e.g. code review tools, diff utilities. And of course, different people use different editors. So editors are very helpful, but I believe we can write clearer code if we don’t necessarily rely on that crutch.

Similarly, some languages also tend to lend themselves better to making code more readable. Type inference and lambda expressions help us make code more succinct and often more readable (though some would argue that explicit typing actually delivers a better experience). The user experience view of code writing is still useful in choosing how to use such language features, where choices are available.


To conclude, considering code writing from a user experience perspective might not be the most natural approach when programming. But if we agree that code readability and clarity is important – directly influencing quality and speed of development – then we should probably look at it from a proven perspective, using considerations and principles otherwise proven for software writing. A programmer’s “code experience” provides another perspective on how code is written and read and should probably be examined when making choices on how to write and structure code. Instead of debating on why a given code is written better this way or that, we can apply user experience guidelines to show us the path to a better code writing.

Pattern Matching in Java?

Writing some code at home, in Java, I came across the problem of trying to compute a value based on the data of another value. This isn’t nothing exciting in on itself, but this whole project I was writing was about trying to write in functional style, as much as possible, in Java 8.
Also, being a fan of fluent interfaces, or readable code in general, this was one of the cases I really missed Scala’s pattern matching capabilities.

So I set to the task of writing a small utility that will allow me to emulate Scala’s pattern matching syntax and behavior, but in Java, at least to some extent.

The end goal I wanted to achieve was to write something similar to:

(you can probably guess the project was something about chess)

In this case p was the parameter passed to a function, which consisted of this call alone. An equivalent piece of code would be to test for the class of p – a series of if-elses, or store this mapping in a map. These are all valid solutions, but I wanted something that would be both concise, and didn’t require extra data preparation. Also something that would be more generally usable than in this case. Besides, I wanted to invent some new way to do this stuff, have some fun doing it.

So I ended up with writing this small utility, which allows for this kind of code:

This code implements a “micro-dsl” of sorts for pattern matching on the data.
The usage of the builder pattern, with 3 internal classes, is to allow for the fluent interface, which was ultimately my goal: enable easy to follow syntax for this kind of operation.

Note that the code makes use of Java 8’s functional interfaces of Predicate and Function, and of course the lambda expression syntax. This allows both for flexibility (you can write any expression you want) as well as concise code.

You can even use it recursively, as the following simple implementation of factorial shows:

It’s not perfect, as it does still tend to be verbose, and not nearly as neat as Scala’s pattern matching, but I believe it does allow for cleaner code, and improves the situation quite a bit for this type of tasks. Note also that this code is pretty simple and self contained – it doesn’t rely on any external library, besides the standard JDK (I did use some trivial utility functions there, e.g. requireNotNull but that’s really beside the point).

Some points where I see this can improve are:

  1. The ability to provide a default match (an “otherwise” case) that will handle all unmatched cases
  2. The ability to provide the data to match as a lazily evaluated function, to allow for optimization (parallel evaluation of the cases?)
  3. A “vectorized” version of this, allowing to specify a pattern match over a complete stream of values, resulting in another stream of values

I will probably do these when I have some more time and the need arises. In the meantime, keeping it simple.

Full source, with updates, is available here.