A defect prediction method for software versioning
Software Quality Control
Profiling the operational behavior of OS device drivers
Empirical Software Engineering
Incorporating qualitative and quantitative factors for software defect prediction
Proceedings of the 2nd international workshop on Evidential assessment of software technologies
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A classic question in software development is "How much testing is enough?" Aside from dynamic coverage-based metrics, there are few measures that can be used to provide guidance on the quality of an automatic test suite as development proceeds. This paper utilizes the Software Testing and Reliability Early Warning (STREW) static metric suite to provide a developer with indications of changes and additions to their automated unit test suite and code for added confidence that product quality will be high. Retrospective case studies to assess the utility of using the STREW metrics as a feedback mechanism were performed in academic, open source and industrial environments. The results indicate at statistically significant levels the ability of the STREW metrics to provide feedback on important attributes of an automatic test suite and corresponding code.