Software defect prediction with Bug-Code analyzer - A data collection tool demo

Empirical software engineering research community aims to accumulate knowledge in software engineering community based on the empirical studies on datasets obtained from the real software projects. Limiting factor to building the theory over thus accumulated knowledge is often related to dataset bias. One solution to this problem is developing a systematic data collection procedure through standard guidelines that would be available to open community and thus enable reducing data collection bias. In this paper we present a tool demonstration that implements a systematic data collection procedure for software defect prediction datasets from the open source bug tracking and the source code management repositories. Main challenging issue that the tool addresses is linking the information related to the same entity (e.g. class file) from these two sources. The tool implements interfaces to bug and source code repositories and even other tools for calculating the software metrics. Finally, it offers the user to create software defect prediction datasets even if he is unaware of all the details behind this complex task.