To write clean code, you must first write dirty code and then clean it.

With pleasure I have been reading Clean Code by Robert C. Martin. The book is a nice read, with short chapters. However, just reading the book has no value. You will need to recognize the “smells and heuristics” in your day to day work, and act on them. This requires labor and dedication, which will gradually enhance your level of experience. The power of this book, at least to me, lies in defining and describing many heuristics, making them easier to recognize.

The book is full of take-aways, and below is a small selection from the book that drew my attention most.

Flag arguments are ugly

Perhaps the only exception is for specific setters that directly set the value of an object property (flag?) itself. But I have to agree that flags implicitly mean that the method is probably doing too much (e.g. there is no Command Query Separation).

Minimize the number of arguments

I had seen the term of dyadic functions before, but the term “dyadic” is hardly used in programming conversations. I also think that when you do use the term, you still have to explain what it means! Let alone “dyads” and “triads”…

Anyway, it is always a good programming advice to minimize the number of arguments. Zero or one argument is easiest to understand and maintain.

Have No Side Effects

Very valuable advice. Simple to understand, and shouldn’t be too hard to implement. Probably sometimes side effects happen when writing a method at first, but during refactoring such “lies” should be taken care of, and removed.

Avoid output arguments

Output arguments are objects that the method operates on, and then returns. An example:

extendWall(h);

Does this function extend “h” with a wall? Or is the wall extended with “h”? And what would it return? It’s more clear to use “this” as the output argument:

h.extendWall();

Command Query Separation

Functions should either do something or answer something. That’s practical and clear advice.

Comments are fails

The author has a clear opinion on comments. He considers every single comment written as a failure, because the code apparently isn’t expressive enough. One reason, which is hard to deny, is that comments are often badly maintained. Investing time in proper and descriptive naming in the code is a rewarding practice. Still, I think it’s fine to explain the “why” of code where code alone simply is not expressive enough to easily understand what’s going on. But the take-away here to me is that “the only truth is in the code”.

The Purpose of Formatting

Your style and discipline survives, even though your code does not.

I’m a big advocate of clear coding standards, but I didn’t take it as far as this. But ultimately, I think this is true. Maintainability and extensibility are always top priority, more so than some implementation details. Still, conventions alone will take you nowhere.

Don’t Pass Null

Simply do not return or pass `null`. It’s better to use “empty” versions of the type that’s being expected, e.g. an empty array, string or object. This way, the receiving code doesn’t have to check the type. Unless you are writing some public, robust API. But internally, it saves a lot of exception handling to minimize such usage of `null` values.

Learning Tests Are Better Than Free

Writing (unit) tests are an absolutely smart way to learn and exercise a (new) interface. It gives a feel about something you need to learn anyway. Tests from both simple and exercising production code can serve as documentation along the way.

Tests Enable the -ilities

It’s the tests that keep our code flexible, maintainable, and reusable […] Because tests enable change.

Think about that for a while, and probably you will appreciate tests even more.

Getting Clean via Emergent Design

Any design is considered “simple” if it:

1. Runs all the tests
2. Contains no duplication
3. Expresses the intent of the programmer
4. Minimizes the number of classes and methods

Making a system testable motivates (or forces) to implement established programming principles, which leads to better designs. Then, the rest follows with incremental refactorings which can be done because of the tests. The take-away for me here is that tests both motivate and catalyse refactoring to better designs.

Conclusion

There are many more principles, patterns, and practices in the book. This list summarizes what stood out for me most. I think any serious programmer will pick up something useful from reading this book. Highly recommended!