Studies show that about 80% of the total effort is spent by a development team especially in software maintenance. Software maintenance addresses bug fixation, new feature implementation or any other type of software change requests by the software users. The maintenance of a software encompasses a wide range of tasks such as program comprehension, concept location, impact analysis, code review, traceability link recovery, and so on. Recommendation systems that exploit the context of a programming problem/task and mine appropriate historical data often can assist the software developers in overcoming such challenges. In my research, I mine large software repositories such as programming Q & A site--Stack Overflow, code repository-- GitHub and Bug repository--BugZilla, and retrieve meaningful insights for recommendation for developers. The baseline idea is to exploit the invaluable technical knowledge created by an extremely large technical crowd.
Bunch of my research projects running. Please consider to cooperate https://github.com/masud-technope/
Q&A for professional and enthusiast programmers
Q&A for peer programmer code reviews
Q&A for meta-discussion of the Stack Exchange family of Q&A websites
Q&A for apps, scripts, and development with the Stack Exchange API
Q&A for users of TeX, LaTeX, ConTeXt, and related typesetting systems
Q&A for pro webmasters