Abstract—The complexity of a program or software can create many difficulties during its lifetime. This complexity entails increased time and effort requirements maintain the code, or discover errors and defects. All of which will lead to an increase in the overall cost of the project. So that, software engineers and developers measure the complexity of program code before they start any project. This paper proposes a novel weighted complexity metric to measure code complexity by using six main attributes. Two of them are a mixture of Cyclomatic, Halsted, and Shao and Wangs metrics. The dataset of this research consists of 15 programs written in Java programming language, and collected from different websites. The programs were ranked by seven experts in Java programming language. Our metric was able to achieve 94% accuracy for results.

Index Terms—complexity metric, cyclomatic, halsted volume, Shao and Wangs metric, software engineering

Cite: Mohammed A. Shehab, Yahya M. Tashtoush, Wegdan A. Hussien, Mohammed N. Alandoli, and Yaser Jararweh, "An Accumulated Cognitive Approach to Measure Software Complexity," Vol. 6, No. 1, pp. 27-33, February, 2015. doi:10.12720/jait.6.1.27-33