Improving enterprise software maintenance efficiency through mining software repositories in an industry context

There is an increasing trend to outsource maintenance of large applications and application portfolios of a business to third parties, specializing in application maintenance, who are incented to deliver the best possible maintenance at the lowest cost. In a typical industry setting any maintenance project spans three different phases; Transition, Steady-State and Preventive Maintenance. Each phase has different goals and drivers, but underlying software repositories or artifacts remain the same. To improve the overall efficiency of the process and people involved in these different phases, we require appropriate insights to be derived from the available software repositories. In the past decade considerable research has been done in mining software repositories and deriving insights, particularly focussed on open source softwares. However, focussed studies on enterprise software maintenance in an industrial setting is severely lacking. In this thesis work, we intend to understand the industry needs on desired insights and limitations on available software artifacts across these different phases. Based on this understanding we intend to propose and develop novel methods and approaches for deriving desirable insights from software repositories. We also intend to leverage empirical techniques to validate our approaches both qualitatively and quantitatively.