The Correlation among Software Complexity Metrics with Case Study
This work addresses software quality assessment for developers and engineers, but appears incremental in analyzing established metrics.
This paper investigates the relationship between software complexity metrics (Cyclomatic complexity, line of code, and Halstead complexity) and software quality, analyzing their correlations and impact on error counts using a real dataset.
People demand for software quality is growing increasingly, thus different scales for the software are growing fast to handle the quality of software. The software complexity metric is one of the measurements that use some of the internal attributes or characteristics of software to know how they effect on the software quality. In this paper, we cover some of more efficient software complexity metrics such as Cyclomatic complexity, line of code and Hallstead complexity metric. This paper presents their impacts on the software quality. It also discusses and analyzes the correlation between them. It finally reveals their relation with the number of errors using a real dataset as a case study.