Algorithm readability and maintainability are crucial aspects of software design that affect the quality, performance, and scalability of your code. In this article, you will learn some effective strategies for writing clear, concise, and consistent algorithms that can be easily understood, modified, and reused by yourself and other developers.
One of the simplest and most important ways to improve algorithm readability and maintainability is to use meaningful names for your variables, functions, classes, and modules. Names should be descriptive, unambiguous, and consistent with the purpose and logic of your algorithm. Avoid using vague, generic, or misleading names that can confuse the reader or cause errors. For example, instead of using x, y, or temp as variable names, use more specific and informative names like index, count, or sum.
Just about all literals should be given meaningful names with comments where possible. That doesn't mean using names like TWO for 2 where there are several occurrences of the number 2 that are actually there for different reasons. Using the name used in public definitions can also help a lot but also keep in mind that even if your current tool chain supports Unicode characters your code may need to be re-used with a tool chain that does not and special characters can be problematic to type, display & print so it is better to use pi or than π for anything other than display purposes. (I was able to type pi immediately but it took me a few minutes to find out how to type π on my machine).
Naming is hard, but it's usually easy to change. So if you come along something and find the name is telling you enough try changing it. Also a dictionary is also a great companion. Often there already is a word for the very thing you try to describe. It might also make sense to think about the role something has what what it is. A Number can be many things an index, count or sum as mentioned.
Coding standards are a set of rules and guidelines that define the style, format, and structure of your code. Following coding standards can help you write more readable and maintainable algorithms by ensuring consistency, clarity, and compatibility across your codebase. Coding standards can vary depending on the programming language, framework, or project you are working on, but they usually cover aspects such as indentation, spacing, comments, naming conventions, and documentation. You can use tools like linters, formatters, or editors to check and enforce coding standards in your code.
I'd recommend to not just follow a coding standard but make it the default with as little steps as possible. Having the same code style settings is good, but having everyone get the settings automatically just by checking out the code is even better. This takes away the burden for new team members or if settings change.
It is also excellent practice to include in each project a note of what the coding standard(s) to be used is and where to find it. This should be in a human readable format, possibly in addition to any tool specific configuration files as not everybody has the same tools, tool versions change, etc.
Abstraction and modularization are techniques that allow you to simplify and organize your algorithm by breaking it down into smaller and more manageable units of functionality. Abstraction means hiding the details and complexity of your algorithm behind a simpler interface or representation. Modularization means dividing your algorithm into separate and independent modules or components that can be reused and combined in different ways. By using abstraction and modularization, you can improve algorithm readability and maintainability by reducing duplication, complexity, and coupling, and increasing cohesion, reusability, and testability.
Comments and documentation are essential elements of algorithm readability and maintainability that provide additional information and explanation about your code. Comments are short notes or annotations that you write within your code to describe what it does, why it does it, or how it does it. Documentation is a more comprehensive and structured description of your code that you write outside your code to provide an overview, specification, or instruction for your algorithm. By using comments and documentation, you can improve algorithm readability and maintainability by making your code more understandable, transparent, and accessible for yourself and other developers.
As there tend to be no tests for comments they can become obsolete with time. Therefore I tend to only write comments where I'm not able to handle it in code. You can extract code into variables of methods to give it a name, which might already be enought. Maybe if there is a pitfall using some code you can refactor so it's not possible to use it the wrong way or can be caught a compiler.
Design patterns and principles are proven solutions and best practices that help you solve common problems and challenges in software design. Design patterns are reusable templates or models that provide a general approach or structure for your algorithm. Design principles are general rules or guidelines that help you make better decisions or trade-offs for your algorithm. By using design patterns and principles, you can improve algorithm readability and maintainability by applying consistent, reliable, and effective solutions that enhance the quality, performance, and scalability of your code.
Refactoring and reviewing your code are processes that help you improve algorithm readability and maintainability by identifying and correcting issues, errors, or inefficiencies in your code. Refactoring means modifying your code without changing its functionality or behavior, but improving its design, structure, or quality. Reviewing means examining your code or having someone else examine your code to find and fix bugs, errors, or flaws. By refactoring and reviewing your code, you can improve algorithm readability and maintainability by eliminating redundancy, complexity, and inconsistency, and increasing clarity, simplicity, and correctness.
Try to write the algorithm in plain mathematical (accurate) English, and move to more granular instructions. Each instruction that you split to more granular ones, should be named meaningfully. This top-down design/coding + meaningful names can make everything simpler to you and everyone else. Additionally, it can improve testability.
Take the stance of the one using the code you're about to write. From this side, how would you want to be able to use it? Pretend it's magic and can do anything you want and try using it as you would wish it existed already. Then try and make it happen.
It can be vital to make it 100% clear which system of units you are using and to use it consistently then make sure that it is used. As the Mars Lander crash showed failure to do so can result in major problems. Note that it is almost always better to explicitly use SI Units and to be aware & beware of local casual units, e.g. a gallon may be an Imperial gallon (4.54609 litres), a US gallon (3.785411784 litres) or a US Dry gallon (4.40488377086 litres).