Evaluating the Accuracy of Different Software Complexity Metrics in Predicting Software Performance.

preprint OA: closed
📄 Open PDF View at publisher

Abstract

To determine the complexity of software systems, software complexity measures are commonly utilized. However, their accuracy in forecasting software performance has been widely disputed. Accuracy of multiple software complexity measures in forecasting software performance are intended to be examined in this research study, employing numerous performance variables such as execution time, memory utilization, and scalability. Cyclomatic Complexity, Lines of Code, Halstead Complexity measures, and maintainability index are the most used methods to measure the complexity of software system. In this research result indicates how that different complexity matrices are vary in giving different software performance. Also examine what are the limitations of this different complexity matrixes.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-07-31T06:42:51.797318+00:00