Software maintenance and evolution is a vital and resource consuming phase of the software lifecycle. Introducing software changes is a particularly complex phenomenon in case of long-lived, large-scale, and globally distributed systems. Years of research efforts have recognized three core tasks to support developers during software maintenance: feature location (a starting point of a change in source code), impact analysis (other software entities that are also change prone), and expert developer recommendations (appropriate developers to implement changes). The research will develop a novel one-stop solution for these tasks by integrating and mining the latent information cluttered in structured and unstructured software artifacts produced and constantly changed during evolution of software systems, which are largely untapped in current solutions.
This research program has three main goals: 1) Define a new integrated framework SE2 for a comprehensive analysis of software evolution, based on conceptual and evolutionary information, under a single umbrella, 2) Define new methodologies for software maintenance tasks based on SE2, and 3) Perform empirical studies to evaluate SE2 and supported methodologies. Central to our solution are the state of the art data mining, information retrieval, and program analysis methods. The research will formulate both theoretical foundations and deliver novel practical solutions to uniformly represent, analyze, and use them within the SE2 framework. Among the broader impacts the project includes production of software tools under open source licenses and collaboration with industry to transfer technology.
