Prioritizing Warning Categories by Analyzing Software History

Automatic bug finding tools tend to have high false positive rates: most warnings do not indicate real bugs. Usually bug finding tools prioritize each warning category. For example, the priority of "overflow " is 1 and the priority of "jumbled incremental" is 3, but the tools 'prioritization is not very effective. In this paper, we prioritize warning categories by analyzing the software change history. The underlying intuition is that if warnings from a category are resolved quickly by developers, the warnings in the category are important. Experiments with three bug finding tools (FindBugs, JLint, and PMD) and two open source projects (Columba and jEdit) indicate that different warning categories have very different lifetimes. Based on that observation, we propose a preliminary algorithm for warning category prioritizing.

1. Introduction

Bug finding tools such as FindBugs [6], JLint [1], and PMD [4] analyze source or binary code and warn about potential bugs. These tools tend to have a high rate of false positives: most warning instances do not indicate real bugs. These tools usually prioritize warning categories to put likely false positives at the bottom of the list, but these tools' prioritization is not very effective [9].