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Software Analysis

Description

Developing software that behaves as expected is challenging not just in practice but also due to the intrinsic complexity of analyzing software properties automatically. Software analysis offers techniques that can work around these hurdles – guaranteeing correctness, or helping find incorrect behavior. This course describes software analysis techniques, highlights their theoretical underpinnings, and presents tools that make them available in practice to the working software engineer. The presentation includes techniques spanning different levels of correctness guarantees, automation, and applicability. The main covered topics are: axiomatic semantics and deductive verification; static analysis and type systems; model checking and predicate abstraction; symbolic execution; and dynamic analysis. The course includes assignments where students apply open-source software analysis tools in practice – understanding the trade-offs involved in making software verification technology applicable in realistic settings.

 

REFERENCES

  • M. Huth, M. Ryan: Logic in computer science. 2nd edition, Cambridge University Press, 2004
  • F. Nielson, H. R. Nielson, C. Hankin: Principles of program analysis. Springer, 2004
  • A. R. Bradley, Z. Manna: The calculus of computation. Springer, 2007
  • B. Pierce: Types and programming languages. MIT Press, 2002
  • A. Zeller: Why Programs Fail: A Guide to Systematic Debugging. Morgan Kaufmann, 2005

People

 

Furia C. A.

Course director

Additional information

Semester
Spring
Academic year
2019-2020
ECTS
6
Language
English
Education
Master of Science in Software & Data Engineering, Core course, Lecture, 1st year

PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (4 ECTS)

PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (4 ECTS)