TU Delft
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2017/2018 Electrical Engineering, Mathematics and Computer Science Master Computer Science
Software Analytics
Responsible Instructor
Name E-mail
Dr. A. Bacchelli    A.Bacchelli@tudelft.nl
Contact Hours / Week x/x/x/x
Education Period
Start Education
Exam Period
Course Language
Expected prior knowledge
Experience with programming (at least scripting languages, such as python) is expected.
Course Contents
Software repositories archive valuable software engineering data, such as source code, execution traces, historical code changes, mailing lists, and bug reports. This data contains a wealth of information about a project's status and history. Doing data science on software repositories, researchers can gain empirically based understanding of software development practices, and practitioners can better manage, maintain and evolve complex software projects.
Study Goals
This course explores techniques and leading research in mining Software Engineering 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 do data science on software repositories in their own research or practice.
Education Method
Frontal lectures with hands-on tutorials. Students will learn techniques of data mining and see how these were practically applied in software engineering context.

Except for the frontal lectures, the expected workload focuses on the lab project, thus accounting for approximately 8/10 hours of work per week, per student.
Literature and Study Materials
Slides and research papers will be at the basis of the course. The teacher will share these resources as study materials with the students.
One original project done alone or in a group of 2 or 3 students. The project will explore one or more of the themes covered in the course from a novel perspective (e.g., on new data). The project will be graded according to originality and interestingness, depth of the work, correctness of the analysis, and the presentation quality of the written (6-page IEEE format) report and accompanying source code.

Since the course is evaluated on a project, there is no possibility for a resit.
Enrolment / Application
Each student who wants to take part in this course is *required* to:
- register/enrol on Blackboard before the start of the course
- participate in the first lecture of the course

Failure to comply with these requirements may lead the student to be not allowed to take part in the course.
Research Methods
Software Engineering