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A Study of Static Warning Cascading Tools (Experience Paper)
May 04, 2023 ยท Entered Twilight ยท ๐ arXiv.org
Repo contents: Experiments_result.xlsx, README.md, real-word-set-result, warnings_sqlite
Authors
Xiuyuan Guo, Ashwin Kallingal Joshy, Benjamin Steenhoek, Wei Le, Lori Flynn
arXiv ID
2305.02515
Category
cs.SE: Software Engineering
Citations
0
Venue
arXiv.org
Repository
https://github.com/WarningCas/WarningCascading_Data
Last Checked
3 months ago
Abstract
Static analysis is widely used for software assurance. However, static analysis tools can report an overwhelming number of warnings, many of which are false positives. Applying static analysis to a new version, a large number of warnings can be only relevant to the old version. Inspecting these warnings is a waste of time and can prevent developers from finding the new bugs in the new version. In this paper, we report the challenges of cascading warnings generated from two versions of programs. We investigated program differencing tools and extend them to perform warning cascading automatically. Specifically, we used textual based diff tool, namely SCALe, abstract syntax tree (AST) based diff tool, namely GumTree, and control flow graph (CFG) based diff tool, namely Hydrogen. We reported our experience of applying these tools and hopefully our findings can provide developers understandings of pros and cons of each approach. In our evaluation, we used 96 pairs of benchmark programs for which we know ground-truth bugs and fixes as well as 12 pairs of real-world open-source projects. Our tools and data are available at https: //github.com/WarningCas/WarningCascading_Data.
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