How to measure Code Complexity?
A simple understanding of Code Complexity and its advantages
The efficiency of a software project is heavily influenced by the complexity of the code. It is easy for code to become complicated.
It can sometimes become so intricate that no major enhancement can be made. In such cases, the only option to improve the code further is to minimize its complexity first.
Here are some of the metrics used to measure code complexity
Source Lines of Code (SLOC)
It counts the number of lines in the source code. It is the most basic metric for determining the scope of a program. However, functionality and complexity do not always go hand in hand, as a talented developer may be able to achieve the same result with far less code.
This metric determines how much control flow is present in a program. Because programs with more conditional logic are more complicated, determining the amount of complexity allows developers to determine how much management is required. This is accomplished by counting the number of pathways that run through the code.
This metric measures how much information is in the source code. It looks at how many variables are used and how often they are used in programs and functions. Since these additional pieces of data affect data flow, programmers must learn them
It determines the overall score of a program’s maintainability. Unlike Cyclomatic complexity and Halstead volume, the maintainability index is more of an empirical measure.
While measuring the code complexity it will also help the developers grow. By understanding why their code is complex, developers learn to improve their code in the future.
To read more about Code Complexity, check out this article — A Simple Understanding of Code Complexity
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