Thesis
Automated configuration of static analysis tools that assess code quality
Washington State University
Master of Science (MS), Washington State University
05/2019
DOI:
https://doi.org/10.7273/000003955
Handle:
https://hdl.handle.net/2376/125437
Abstract
Developers often use static code analysis tools to automatically detect flaws in the quality of their code. These tools generally display too many false positives which reduce their effectiveness. There have been numerous approaches to improve the effectiveness of the tools such as analysis of source code history to determine proper configuration of the tool and clustering similar warnings. There are limitations to these approaches. For instance, using history of warnings resolved during software evolution can be misleading as some warnings could be removed due to deletion of a block of code or due to refactoring. Clustering similar warnings makes the process of validating the warnings easier but does not actually reduce the false positives. To the best of our knowledge, no one has studied how well the tools can be configured using information extracted from software artifacts that discuss code quality issues. In this work, we study how well static code analysis tools can be configured using code review comments by mining code review repository of six open-source Java projects from Gerrit. We are able to infer appropriate checks from code review comments with a micro-averaged precision of 78% and macro-averaged precision of 80%.
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Details
- Title
- Automated configuration of static analysis tools that assess code quality
- Creators
- Saghan Mudbhari
- Contributors
- Venera Arnaoudova (Advisor) - Washington State University, School of Electrical Engineering and Computer Science
- Awarding Institution
- Washington State University
- Academic Unit
- School of Electrical Engineering and Computer Science
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Identifiers
- 99900890805101842
- Language
- English
- Resource Type
- Thesis