Seminar: Static Program Analysis -- Foundations and Concepts


  • The Kick-Off is scheduled for October 29th, 11.00h until 11.45 in room IZ 349 (tentative).

Organizational Matters

Prof. Dr.-Ing. Ina Schaefer
Benjamin Schmidt, Dipl.-Inform.
Sönke Holthusen, M.Sc.
Credits: Depends on the major and your exam regulations, one CP = 30h of work.
Audience: Bachelor and master students studying computer science, business informatics or IST who are interested in scientific work.
Registration: Use StudIP to register yourself for the seminar. We have limited our capacities to a maximum of 10 attendees!

For a successful participation, the following tasks have to be fulfilled:

  • Written paper about your topic (Bachelor: 6-8 pages, Master: 8-10; both in ACM double column style).
  • 25-30 minutes talk about your topic and discussion.
  • Review of two other papers.
  • Mandatory participation of all events.
Prerequisites: Generally, no prerequisites are required for attending the course. However, students should be able to work on the selected topic autonomously in order to understands the insights. Moreover, it is a plus (although not mandatory) if students have a good understanding of formal math or prior knowledge/experience with formal aspects of programming languages (e.g., Compiler I).



  • The kick-off for the seminar is held (tentative, subject to change) on October 29th, 11.30h in room IZ 349 (ISF library).
  • Additional dates are announced via StudIP.



The following topics are available. Literature

  1. Code Metrics (Bachelor)
  2. Practical Data-Flow Analysis (Bachelor)
  3. Monotone Frameworks (Master)
  4. Static Program Slicing (Bachelor)
  5. Pattern-based Bug Detection (Bachelor)
  6. Call String Based Interprocedural Analysis (Master)
  7. Graph-based Interprocedural Frameworks (Master)
  8. Points-to Analysis (Master)
  9. Data-flow Analysis of Software Product Lines (Master)
  10. Abstract Interpretation (Master)

For each topic the following aspects should be considered and discussed (if applicable).

  • Motivation
  • Foundations/basic concepts
  • Main aspects of the topic, e.g.
    • Application domain
    • Method/technique
    • Validity/expressiveness of the analysis
    • Precision, correctness, completeness
    • Complexity
    • Limitations
    • Tools/implementations currently in use
Hint: A large amount of this lecture is based on independent work. You should prepare yourself for one work day a week to handle the workload.

Learning objectives and achievable skills

The following skills are achieved in this course:

  • An organized approach to search, read and understand scientific literature.
  • A structured prepearation of the achieved insights.
  • Communication of the achieved results in a talk given in front of the other participants.
  • Personal scheduling of tasks.

  last changed 30.06.2015
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