COURSE OVERVIEW
Software engineering data (such as code bases, execution traces, historical code changes, mailing lists, and bug databases) contains a wealth of information about a project's status and history. Using well-established data mining techniques, researchers can gain empirically based understanding of software development practices, and practitioners can better manage, maintain and evolve complex software projects.

COURSE OBJECTIVES
This seminar course explores leading research in mining Software Engineering (SE) data, discusses challenges associated with mining SE data, highlights SE data mining success stories, and outlines future research directions. Students will acquire the knowledge needed to perform research or conduct practice in the field. Once completed, students should be able to integrate SE data mining techniques in their own research or practice.

QUEEN'S

• CISC 880: Mining Software Engineering Data [Fall 18]

• CISC 880: Mining Software Engineering Data [Fall 17]

• CISC 880: Mining Software Engineering Data [Fall 16]

• CISC 880: Mining Software Engineering Data [Fall 15]

• CISC 880: Mining Software Engineering Data [Fall 14]

• CISC 880: Mining Software Engineering Data [Fall 11]

• CISC 880: Mining Software Engineering Data [Fall 10]

• CISC 880: Mining Software Engineering Data [Fall 09]

• CISC 880: Mining Software Engineering Data [Fall 08]

• CISC 864: Mining Software Engineering Data [Fall 07]