Code efficiency increases speed while reducing the percentage of errors in a developer’s code lines or base. This means you will be able to code more in less time and produce deliverables without glitches. The term ‘code efficiency’ is also highly integrated with the concept of algorithmic efficiency and runtime speed. Additionally, there are several tools to help you measure your coding proficiency. Want to know what they are? In this article at Medium, Kelly Becker shares how developers can determine their code efficiency to make their resource hours more productive.
How to Validate Code Efficiency
Since more advanced technologies are becoming common office jargon nowadays, it is all the more important for you as a developer to grow. Artificial intelligence, machine learning, etc., need a perfect codebase and less turnaround time to work efficiently for a company. So, let’s find out how the following guidelines can increase code efficiency and improve your daily developer productivity:
Big O Notation
Programmers use this tool to detect their algorithmic performance and efficacy. Becker adds, “It is used to determine the worst-case scenario for time required, or space used to complete execution of an algorithm.”
Time vs. Space Complexity
Big O Notation also measures time and space complexities. Time complexity is the cluster of smaller operations you must perform to complete the entire task. Whereas space complexity, commonly termed auxiliary space complexity, is the extra memory you need to run the code lines in an algorithm for code efficiency.
Sub-Categories of Time Complexity
You can subdivide time complexity. The standard types are constant, logarithmic, linear, linearithmic, and quadratic.
Complexity Operational Rules
- For time complexity, ensure that the arithmetic operations, accessing elements in arrays, and variable assignment are constant. Additionally, Becker points out, “In a loop, the complexity is the length of the loop times the complexity of whatever happens inside that loop.”
- For space complexity, primitives such as booleans, numbers, undefined, and null are constant. Strings need O(n) space, where ‘n’ specifies the string length.
To view the original article in full, click on the following link: https://medium.com/swlh/be-an-effective-and-efficient-programmer-aabde20c673e