Mining Software Repositories to Understand the Performance of Individual Devel

Version control information can be enhanced with the data from defect tracking systems and archived communications. All the information sources together lead to an extensive data set, which can help individual developers to drive changes to personal development behavior. However, the formats of and access to these information vary considerably across different software repositories that complicates the integration of these data. Furthermore, the raw information obtained from repositories is too large to provide deep insight into the software evolution at the developer level, and hence poses difficulties for researchers in carrying out a quantitative data analysis In this paper, we outline our experiences mining and merging the individual-related data from some popular software repositories. Then we adopt a multi- criteria analysis model, data envelopment analysis (DEA) to analyze the collected data based on the predefined metrics.