The main research agenda of COINSE lab is the application of computational intelligence to problems in software engineering. Various kinds of meta-heuristic optimisation and machine learning techniques have been applied to software engineering, in order to either provide valuable insights into complicated trade-offs between issues or automate repetitive and error-prone human practices. Broadly, this movement of applying meta-heuristic optimisation to software engineering has been called SBSE (Search-Based Software Engineering) and has been steadily growing over the past decade.

We sit in the cross section of computational intelligence research and software engineering research. The techniques we are interested in include, but are not limited to, local search, evolutionary algorithm, genetic programming, and Monte-Carlo methods. The problem domains we are interested in include, but also are not limited to, software testing, requirements engineering, automated debugging, and app-store analysis. The lab pursues both empirical and theoretical approaches to SBSE.