Module: Model Checking - Proof Engines and Algorithms
|Model Checking - Proof Engines and Algorithms||Lecture||2||Summer Semester|
|Model Checking - Proof Engines and Algorithms||Recitation Section (small)||2||Summer Semester|
Prof. Görschwin Fey
Recommended Previous Knowledge:
Basic knowledge about data structures and algorithms
- algorithms and data structures for model checking,
- basics of Boolean reasoning engines and
- the impact of specification and modelling on the computational
effort for model checking.
- explain and implement algorithms and data structures for model checking,
- decide whether a given problem can be solved using Boolean reasoning or model checking, and
- implement the respective algorithms.
- discuss relevant topics in class and
- defend their solutions orally.
Using accompanying material students independently learn in-depth relations between concepts explained in the lecture and additional solution strategies.
ECTS-Credit Points Module:
Workload in Hours:
Independent Study Time: 124, Study Time in Lecture: 56
Course: Model Checking - Proof Engines and Algorithms
German & English
Correctness is a major concern in embedded systems. Model checking can fully automatically proof formal properties about digital hardware or software. Such properties are given in temporal logic, e.g., to prove "No two orthogonal traffic lights will ever be green."
And how do the underlying reasoning algorithms work so effectively in practice despite a computational complexity of NP hardness and beyond?
But what are the limitations of model checking?
How are the models generated from a given design?
The lecture will answer these questions. Open source tools will be used to gather a practical experience.
Among other topics, the lecture will consider the following
Modelling digital Hardware, Software, and Cyber Physical Systems
Data structures, decision procedures and proof engines
Binary Decision Diagrams
Satisfiability Modulo Theories
System Verilog Assertions
Symbolic CTL Checking
Bounded LTL-Model Checking
Optimizations, e.g., induction, abstraction
Edmund M. Clarke, Jr., Orna Grumberg, and Doron A. Peled. 1999. Model Checking. MIT Press, Cambridge, MA, USA.
A. Biere, A. Biere, M. Heule, H. van Maaren, and T. Walsh. 2009. Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, The Netherlands, The Netherlands.
Selected research papers