Quality assurance - Regression testing and fault prediction
- 2.5 credits
- Second cycle (A1N)
- Main area: Computer Science
- School of Innovation, Design and Engineering
- Course code: DVA466
Changes to software under test are unavoidable. Such changes and their side effects must be well tested, without re-running all tests. Moreover, in general, testing cost is well known, therefore faults must be detected early by focusing testing efforts on fault-prone parts. The participants in the course will learn about regression test selection and software fault prediction techniques. Effective regression test selection techniques will reduce cost of implementing modifications to software under test. Software fault prediction part of the course is about focusing test efforts on more fault-prone parts of the software where maximum return on investing test resources can be achieved. Overall, this course is about using techniques that make software testing more efficient and effective.
This is a course at advanced level for those with University credits and work experience. It is developed to suit professionals who need to be able to combine work and studies.
Further information about the course at: http://www.promptedu.se
Read all about how to apply here: http://www.promptedu.se/f
Autumn semester 2019, Ortsoberoende, week 36 - 3
- 10%, mixed
- Location: Online
- week 36 - 3
- Language of instruction: English
- Apply code: MDH-24142
Application is opened one month before the last closing day for enrolments.
At least 100 credits, out of which 70 credits are within technology or information technology, with at least 15 credits in programming or software development.
In addition Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.
Course syllabus and literature
Applicants with at least 12 month (full-time) documented work-experience from software development have priority. Other applicants are ranked by university credits.