A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
IEEE Software
Is Software Quality Visible in the Code?
IEEE Software
Critical Success Factors In Software Projects
IEEE Software
IEEE Security and Privacy
Static analysis tools as early indicators of pre-release defect density
Proceedings of the 27th international conference on Software engineering
An industrial case study of classifier ensembles for locating software defects
Software Quality Control
An iterative semi-supervised approach to software fault prediction
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
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The number of defects is an important indicator of software quality. Agile software development methods put an explicit requirement on automation and permanently low defect rates. Code analysis tools are seen as a prominent way to facilitate the defect prediction. There are only few studies addressing the feasibility of predicting a defect rate with the help of static code analysis tools in the area of embedded software. This study addresses the usefulness of two selected tools in the Symbian C++ environment. Five projects and 137 KLOC of the source code have been processed and compared to the actual defect rate. As a result a strong positive correlation with one of the tools was found. It confirms the usefulness of a static code analysis tool as a way for estimating the amount of defects left in the product.