Code Quality Evaluation Methodology Using The ISO/IEC 9126 Standard
Authors: Yiannis Kanellopoulos (University of Manchester, U.K), Panos Antonellis (University Of Patras, Greece), Dimitris Antoniou (University Of Patras, Greece), Christos Makris (University Of Patras, Greece), Evangelos Theodoridis (University Of Patras, Greece), Christos Tjortjis (Univ. of Ioannina, Greece and), Nikos Tsirakis (University Of Patras, Greece)
AI-generated Key Points
- The paper presents a methodology for evaluating the quality of source code and its static behavior in a software system, using the ISO/IEC-9126 standard as a basis.
- The proposed approach employs elements automatically derived from source code, enhanced with expert knowledge in the form of quality characteristic rankings.
- The methodology is highly flexible, allowing for customization of metrics and source code attributes employed, as well as the specific ISO/IEC-9126 characteristics to be assessed.
- The approach can capture software quality trends and express expert perceptions concerning system quality in a quantitative and systematic manner.
- The methodology enables software engineers to evaluate both internal (source code) and external (user-perceived) quality factors in an integrated manner.
- It allows for easy customization based on project-specific requirements or preferences.
- It provides a clear framework for assessing software quality that can be easily communicated to stakeholders.
Abstract: This work proposes a methodology for source code quality and static behaviour evaluation of a software system, based on the standard ISO/IEC-9126. It uses elements automatically derived from source code enhanced with expert knowledge in the form of quality characteristic rankings, allowing software engineers to assign weights to source code attributes. It is flexible in terms of the set of metrics and source code attributes employed, even in terms of the ISO/IEC-9126 characteristics to be assessed. We applied the methodology to two case studies, involving five open source and one proprietary system. Results demonstrated that the methodology can capture software quality trends and express expert perceptions concerning system quality in a quantitative and systematic manner.
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