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. Only 6%, 9%, and 9% of warnings are removed by bug fix changes during 1 to 4 years of the software development. About 90% of warnings remain in the program or are removed during 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 highpriority warning instances is only 3%, 12%, and 8% respectively. 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 wa...
Sunghun Kim, Michael D. Ernst