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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Marchenko, A., & Abrahamsson, P. (2007). Predicting software defect density: A case study on automated static code analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4536 LNCS, pp. 137–140). Springer Verlag. https://doi.org/10.1007/978-3-540-73101-6_18
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