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

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This is the website of a past course.

The next course in the ALP series is ALP 2012.

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 Wednesday, 8:15-9:45.
Date Weekly, from April 6 to July 13 (except for June 15 and July 6)
Place Room A207, on the second floor of the “Altbau”, Römerstr. 164.
Course number (Module handbook) MA-INF 3207
Course number (BASIS) 612113207 (Course) and 612213207 (Exercises)
Credit points 6 = 2 (Course) + 4 (Exercises)
Diploma category B (DPO 1998) / B3 (DPO 2003)
Exam: Requirements Formal requirements
Exam: Date, Time, Place See calendar overview sent to the alp_course list.
Language English
Lecturer Dr. Günter Kniesel


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.
  • Clocksin, W.F. (1997). Clause and Effect: PROLOG Programing for the Working Programmer. Berlin: Springer-Verlag. - available at amazon within a few days
  • Bratko, I. (1986). PROLOG: Programming for Artificial Intelligence. Addison-Wesley. - out of print, a new edition is announced for November 2009.
  • Shoham, Y. (1994). Artificial Intelligence Techniques in PROLOG. Morgan Kaufmann. - out of print
  • Shapiro, E., Sterling, L. (1994). The Art of PROLOG. MIT Pr. - availably at amazon
  • Clocksin, W.F., Mellish, C.S. (2003). Programming in Prolog Using the ISO Standard. Berlin: Springer-Verlag - available at amazon


teaching/lectures/alp/2011/start.txt · Last modified: 2018/05/09 01:59 (external edit)

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