Writing Efficient Computer Code
Whether it is C++, Rust, Python, Ruby, or even Dart, programming languages are becoming increasingly more prominent in software development and play a huge role in code efficiency. Though, what is code efficiency? It basically refers to the ability of a computer program to execute its intended tasks in a manner that minimizes resource usage, such as memory, CPU time, and other system resources. It can ultimately have a say in the developed program’s responsiveness, performance, and overall user experience.
When considering code efficiency, one major aspect to consider is algorithmic complexity. This refers to how the execution time of a program expands as the input time increases. Generally, algorithms with lower time complexity are efficient because they can handle large inputs without increasing the execution time by much. In computer language, this is regarded as Big O Notation, including but not limited to O(1), O(log N), O(N log N), O(N).
Though not directly related to the newer programming languages, time complexity is important in terms of utilizing less memory and managing memory allocation to avoid running out of available memory. Now, relatively new languages such as Python utilize shortened algorithm selections, which greatly impact efficiency directly because of the amount of time taken to write code. Python’s built-in operations provide a convenient, but not always optimized, method to be coding. Although, computer languages like C use specialized libraries or manual memory management which can be more effective at times.
Moving on, minimizing input and output operations can often improve efficiency because writing to disk can often be a slow process. Comparatively, in-memory operations like data manipulation, searching and sorting, function calls, and caching will be able to store data quickly.
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Written by Vinay Devarakonda
