Leveraging software analytics to maximize developer productivity during software maintenance.

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Software practitioners make technical and business decisions based on the understanding they have of their software systems. This understanding is grounded in their own experiences, but can be augmented by studying various kinds of development artifacts, including source code, bug reports, version control meta-data, test cases, usage logs, etc. Unfortunately, the information contained in these artifacts is typically not organized in the way that is immediately useful to developers' everyday decision making needs. To handle the large volumes of data, many practitioners and researchers have turned to analytics.***This research program aims to explore how we can systematically uncover the benefits of software analytics in supporting software developers' daily decision-making and improving their awareness and effectiveness when they build and maintain software systems. This program will investigate techniques for gathering, preprocessing, transforming and modelling the data from various development artifacts (bug reports, commit history, source code, maintenance tasks, test suits, developer discussions, etc.) with the purpose of highlighting useful information and drawing conclusions from it.***This project is a part of of a long-term research agenda with the goal of improving the understanding of how developers create, evolve and maintain software systems, and investigating how the practice of software maintenance can be improved.***Software is made by people; and thus, we believe that by better understanding how people create, use and reason about software systems, we can enhance their effectiveness as they develop software. By making tools and development environments more analytics-based, we can improve individual performance and productivity. *** **