As a software developer, you want your code to run fast, smooth, and reliable on different platforms and environments. But how do you optimize your code for various scenarios, such as web, mobile, desktop, cloud, or embedded systems? In this article, we will explore some code optimization techniques that can help you improve your software design and performance.
One of the first steps to optimize your code is to choose the right programming language and tools for your project. Different languages have different strengths and weaknesses, such as speed, memory usage, portability, readability, and compatibility. For example, C and C++ are fast and low-level languages that can run on many platforms, but they require more manual memory management and error handling. Python and Ruby are high-level and expressive languages that can simplify development, but they consume more resources and may not be suitable for performance-critical applications. You should also consider the tools and frameworks that support your language, such as compilers, libraries, IDEs, and testing tools. They can help you write, debug, and optimize your code more efficiently.
In my experience, the first and most important aspect to consider, in order to have high performance software, it’s the architecture of such software, not the programming language. Sure programming languages may allow (or forbid) certain architectural forms, and they also may account for a small performance improvement when dealing with specific form of software design, but the architecture of a piece of software will always account for the largest amount of performance gain or decrease.
Another way to optimize your code is to follow coding standards and best practices that ensure your code is consistent, readable, maintainable, and secure. Coding standards are guidelines that define how to write, format, and document your code, such as naming conventions, indentation, comments, and code structure. Best practices are recommendations that help you avoid common pitfalls and errors, such as memory leaks, buffer overflows, code duplication, and spaghetti code. By following coding standards and best practices, you can reduce bugs, improve code quality, and make your code easier to understand and modify.
In my opinion, when we talk about performance, following standards (especially those surrounding code readability) won’t necessarily lead to better performances unless the specific compiler can truly deal with such code patter in the best way for a given platform (and this is not always the case for all platforms). If I may suggest, it would be probably wise if this article title would be changed into “writing software that is robust and maintainable” instead of focusing on performance given the points made so far, given the article seems to be copied from the typical concepts on the matter of writing maintainable code, just my 0.5c
Design patterns and principles are proven solutions and strategies that help you solve common software design problems and challenges. They can help you optimize your code by making it more modular, reusable, scalable, and adaptable. For example, the SOLID principles are a set of guidelines that help you design your classes and objects in a way that promotes cohesion, coupling, abstraction, inheritance, and polymorphism. The MVC pattern is a framework that helps you separate your application logic into three components: model, view, and controller. By using design patterns and principles, you can improve your code architecture and organization, and make it easier to extend and test.
One of the most important steps to optimize your code is to test and measure your code performance regularly and systematically. You can use various tools and methods to analyze your code behavior, such as profiling, benchmarking, debugging, and logging. Profiling is a technique that measures how much time and memory your code consumes in different parts and functions. Benchmarking is a technique that compares your code performance with other alternatives or standards. Debugging is a technique that identifies and fixes errors and bugs in your code. Logging is a technique that records and monitors your code events and activities. By testing and measuring your code performance, you can identify and eliminate bottlenecks, inefficiencies, and anomalies.
I agree with this point. So far, this is probably the only real good advice to write software that can have good performance. Also, it’s hard to help because what the “author” means with the terms performance is not very clear, so, another suggestion would be adding a section explaining what the term performance means in this particular context?
After testing and measuring your code performance, you can apply optimization techniques and strategies to enhance its speed, memory, reliability, and compatibility. These strategies include reducing the number and size of variables, using faster algorithms and data structures, avoiding unnecessary calculations and operations, caching results, parallelizing tasks, minifying and compressing code, using native code or libraries, and adapting to different platforms. However, be mindful not to over-optimize your code or sacrifice readability, maintainability, or security for performance. It is also important to test and measure the impact of your optimization techniques and strategies before applying them.
This point it’s clearly describing some architectural elements like memoization for example, so maybe you want to change “apply” with refactor or redesign your initial ideas to be more performant?
The last step to optimize your code is to keep learning and improving your skills as a software developer. Software design and development are dynamic and evolving fields that require constant updating and adaptation. You should always be curious and open-minded about new technologies, trends, and innovations that can help you improve your code quality and performance. You should also seek feedback and advice from other developers, mentors, and experts who can help you learn from their experiences and insights. By keeping learning and improving your skills, you can optimize your code for different platforms and environments more effectively and efficiently.
I agree with this point. Learning is key, for instance, to learn how to write extremely performant code, one should learn how code is actually executed on a given system/platform, in order to be able to take the correct architectural and design decisions.
I think everything above can fall under the generic category of 'how to write good code'. None of it specifically addresses the unique requirements of working with specific/differing platforms/environments. Things like RAM size, virtual memory, local/network storage, CPU speed and caches, dedicated/time-shared environments, single/multi-core CPU, wire/portable(i.e. battery) powered, etc. are all issues to be reviewed and understood to effectively deploy on different systems. These are the relevant issues.
Conducting code reviews with team members who may suggest better design or architectural changes, is a good way to improve on programming practice. Also, practice "extreme programming" with another software engineer to catch bugs early and in the process enable thoughtful design, architectural, and programming decisions. Extreme programming (XP) is a software development methodology intended to improve software quality and responsiveness to changing customer requirements.