2009 International Conference on Software Testing Verification and Validation The Effectiveness of Automated Static Analysis Tools for Fault Detection and Refactoring Prediction Denver, Colorado April 01-April 04 ISBN: 978-0-7695-3601-9
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICST.2009.21
Many automated static analysis (ASA) tools have been developed in recent years for detecting software anomalies. The aim of these tools is to help developers to eliminate software defects at early stages and produce more reliable software at a lower cost. Determining the effectiveness of ASA tools requires empirical evaluation. This study evaluates coding concerns reported by three ASA tools on two open source software (OSS) projects with respect to two types of modifications performed in the studied software CVS repositories: corrections of faults that caused failures, and refactoring modifications. The results show that fewer than 3% of the detected faults correspond to the coding concerns reported by the ASA tools. ASA tools were more effective in identifying refactoring modifications and corresponded to about 71% of them. More than 96% of the coding concerns were false positives that do not relate to any fault or refactoring modification.
Index Terms:
static analsis tools, defect prediction, refatoring, open source software, coding concerns, anomaly detection, empirical evaluation
Citation:
Fadi Wedyan, Dalal Alrmuny, James M. Bieman, "The Effectiveness of Automated Static Analysis Tools for Fault Detection and Refactoring Prediction," icst, pp.141-150, 2009 International Conference on Software Testing Verification and Validation, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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