ChangeChecker: A Tool for Defect Prediction in Source Code Changes based on Incremental Learning Method

In software development process, software developers may introduce defects as they make changes to software projects. Being aware of introduced defects immediately upon the completion of the change would allow software developers or testers to allocate more resources of testing and inspecting on the current risky change timely, which can shorten the process of defect finding and fixing effectively. In this paper, we propose a software tool called ChangeChecker to help software developers predict whether current source code change has any defects or not during the software development process. This tool infers the existence of defect by dynamically mining patterns of the source code changes in the revision history of the software project. It mainly consists of three components: (1) incremental feature collection and transformation, (2) real-time defect prediction for source code changes, and (3) dynamic update of the learning model. The tool has been evaluated in a large famous open source project Eclipse and applied to a real software development scenario.