Software Complexity Analysis with the Advanced CB Metric

This study introduces the Refined CB (RCB) metric, an advanced complexity measure for object-oriented software that extends the traditional CB metric by incorporating additional factors like dynamic memory access, compound conditions, and try-catch blocks. The RCB metric significantly enhances the assessment of software complexity, reflecting the cognitive challenges inherent in modern software architectures. By offering a more comprehensive and detailed analysis, the RCB metric contributes to the body of knowledge by providing a nuanced evaluation tool that captures the intricacies of contemporary programming practices. This metric not only improves theoretical understanding but also aids developers in identifying high-complexity areas, thus enhancing code maintainability and quality assurance. The study's findings demonstrate the RCB metric's practical significance as a valuable tool in advancing software quality, offering a robust framework for future research and real-world application in diverse programming environments.

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Published
2024-11-18
DOI
https://doi.org/10.1109/ict4da62874.2024.10777285
Primary Topic
Software Engineering Research
Type
article
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article

Software Complexity Analysis with the Advanced CB Metric

Thathsarani H. A. N. N
Software Engineering Research
article

Software Complexity Analysis with the Advanced CB Metric

Thathsarani H. A. N. N
article en

Abstract

This study introduces the Refined CB (RCB) metric, an advanced complexity measure for object-oriented software that extends the traditional CB metric by incorporating additional factors like dynamic memory access, compound conditions, and try-catch blocks. The RCB metric significantly enhances the assessment of software complexity, reflecting the cognitive challenges inherent in modern software architectures. By offering a more comprehensive and detailed analysis, the RCB metric contributes to the body of knowledge by providing a nuanced evaluation tool that captures the intricacies of contemporary programming practices. This metric not only improves theoretical understanding but also aids developers in identifying high-complexity areas, thus enhancing code maintainability and quality assurance. The study's findings demonstrate the RCB metric's practical significance as a valuable tool in advancing software quality, offering a robust framework for future research and real-world application in diverse programming environments.

Hatch (Canada) (CA)
Openalex Percentile: Top 65%
Software Engineering Research
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