Software Engineering for Smart Data Analytics & Smart Data Analytics for Software Engineering

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ALP General Information

This course is regularly offered in the summer semester, as part of the ICM track of the CS Master's program. The course number in the master module handbook is MA-INF 3207. It should be preferably attended in the second semester of your studies. The course can also be attended by diploma students.

Time Monday, 13:00 - 14:30 s.t.(!). For exceptions see the ROOTS-Teaching Calendar
Place Room 6c, on the ground floor of the “Altbau”, Römerstr. 164.
Course number MA-INF 3207
Credit points 4
Diploma category B
Exam See exam page
Exercise groups See calendar link on exercise page
Language English
Lecturer Dr. Günter Kniesel
Student teaching assistant Eva Stöwe


  • 2009-05-11: Added slides 2-38 through 2-88 to Chapter 2 for today's lecture.


This course adresses people interested in software quality. It shows how very powerful software analysis (for assessing software quality or emerging problems) and software transformation (for automating correction of identified problems) can be built on the basis of declarative model transformation infrastructures that go beyond classical logic programming. In particular, we analyse and transform Java programs using JTransformer.

Since this is an advanced course, we will not spend too much time on logic programming foundations – just a few short sessions that should make you familiar with the used development environment, help you refresh prior knowledge and make sure that all course participants have a comparable starting level. If you have no background in logic programming you will need to invest more time in this initial phase.

The course will lay the foundations for a logic programming representation of arbitrary software systems and will introduce JTransformer as a tool that automatically generates such a representation for arbitrary Java programs. With JTransformer, we will implement various software quality analyses. These analyses will be the use cases that motivate the need for the different advanced logic programming techniques that will gradually be introduced (for instance, metaprogramming, abstract interpretation and partial evaluation).

Finally we will learn about the approach of classic Prolog systems to program transformation, analyse its risks and embrace the alternative concept of “conditional transformations” implemented in the CTC and JTransformer.

Summarizing, you will learn new things in three different areas:

  • advanced logic programming techniques,
  • advanced logic programming for software analysis,
  • advanced logic-based software and model transformation.


teaching/lectures/alp/2009/start.txt · Last modified: 2018/05/09 01:59 (external edit)

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