| Abstract | Automatic bug-finding tools have a high false positive rate: most warnings do not indicate real bugs. Usually bug-finding tools assign important warnings high priority. However, the prioritization of tools tends to be ineffective. We observed the warnings output by three bug-finding tools, FindBugs, Jlint, and PMD, for three subject programs, Columba, Lucene, and Scarab. changes during 1 to 4 years of the software development. About non-fix changes –- likely false positive warnings. The tools' warning prioritization is little help in focusing on important warnings: the maximum possible precision by selecting high-priority \par In this paper, we propose a history-based warning prioritization algorithm by mining warning fix experience that is recorded in the software change history. The underlying intuition is that if warnings from a category are eliminated by fix-changes, the warnings are important. Our prioritization algorithm improves basefilename = "prioritize-warnings-fse2007 |
