What are good software tests? How can we automatically generate them? In this course we will discuss possible metrics for test quality and will present various approaches to automatically generate good tests according to the discussed metrics. Additional topics include the assessment of test outcomes and test maintenance. The concepts presented in this lecture will be applied in 4 practical projects that involve the implementation of test generation approaches in Python.
|Type:||Advanced Lecture (6 Credit Points)|
|Time:||Thu 14:00 — 16:00|
|Tue 14:00 — 16:00 (auxiliary dates)|
|Location:||Building E1.3 Lecture Hall 1 (2 for auxiliary dates)|
|Tutorials:||Tue 16:00 — 18:00 (Building E1.3 Seminar Room 015)|
|Wed 10:00 — 12:00 (Building E1.3 Seminar Room 107)|
|Thu 10:00 — 12:00 (Building E1.3 Seminar Room 014)|
|Thu 16:00 — 18:00 (Building E1.3 Seminar Room 015)|
All resources (slides, exercise sheets, news) for this lecture are accessible from within the course Redmine. Make sure to "watch" the News feed in order to immediately get important information.
|Lecturer:||Prof. Dr. Andreas Zeller|
|Tutors:||Alexander Kampmann||Michael Backenköhler|
For students that have not yet worked with Python here are a few links that can help you to lear about the programming language.
|Python for Java Programmers:||https://www.udacity.com/wiki/python_for_java_programmers|
|Official Python 2 Tutorial:||https://docs.python.org/2/tutorial/|