Our research interests and publications are in Software Engineering with a specific focus on software maintenance and evolution, data-driven and empirical software engineering, mining software repositories, mobile software engineering, program comprehension, software analytics, software data analytics, source code analysis, and software visualization.

The mission of our lab is to improve expressiveness (e.g., structure, semantic, and history aware) and effectiveness (e.g., improve cost, quality, and productivity) of software maintenance and evolution tasks. The developed methodology consists of lightweight parsing and analysis methods, heuristics, and the application of data-mining techniques.  Development of empiric methods and software tools that uncover relationships and pertinent information from developer-centric software artifacts is of key interest.  These uncovered assets, e.g., from past changes recorded in software repositories and linguistic analysis of textual elements, are used to support the future evolution of software systems.