Code Comprehending Measure (CCM)

Gurdev Singh; Satinderjit Singh; Monika Monga

doi:10.24297/ijct.v2i1.6733

Authors

Gurdev Singh Professor and Head Department of Computer Science & Engineering, Adesh Institute of Engineering & Technology, Faridkot
Satinderjit Singh Associate Professor and Head Department. of Computer Application GGNIMT, Civil Lines, Ludhiana
Monika Monga Assistant Professor: Department of Computer Science & Engineering, Adesh Institute of Engineering & Technology, Faridkot

DOI:

https://doi.org/10.24297/ijct.v2i1.6733

Keywords:

Software Complexity, Complexity Metrics, Cognitive Weights, Data Flow Factor, Data Volume Factor

Abstract

Software complexity, accurately, plays a vital role in life cycle of the software. Many metrics have been proposed in the past like LOC, McCabes cyclomatic measure, Halsteads measures and cognitive measures. This paper proposes a new method to measure the software complexity, by not only taking into account the internal structure of the algorithm in terms of the total cognitive weights of the basic control structures but also by quantifying the flow of data between the various basic control structures and data volume factor (variables and perators) used within basic control structure. The preliminary tests show that this metrics is independent of the existing measures. Comparison with some existing measures has been done to prove the robustness of this new metrics.