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Software Metric Analysis of Open-Source Business Software

DOI: 10.4236/jsea.2023.165008, PP. 144-153

Keywords: Open-Source Software, Software Quality, Software Risks, Cyclomatic Complexity, Essential Complexity, Module Design Complexity, Design Complexity, Integration Complexity, Local Data Complexity, Public Global Data Complexity, Parameter Data Complexity, Risk Score, Risk Classification

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Abstract:

Over the past decade, open-source software use has grown. Today, many companies including Google, Microsoft, Meta, RedHat, MongoDB, and Apache are major participants of open-source contributions. With the increased use of open-source software or integration of open-source software into custom-developed software, the quality of this software component increases in importance. This study examined a sample of open-source applications from GitHub. Static software analytics were conducted, and each application was classified for its risk level. In the analyzed applications, it was found that 90% of the applications were classified as low risk or moderate low risk indicating a high level of quality for open-source applications.

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