Lecture Goals:

• Efficient Methods for SAT Solving:
  • Algorithms, Heuristics, Data Structures, Implementation Techniques, Parallelism, Proof Systems
• Applications of SAT Solvers:
  • Verification of Hardware and Software, Planning, Scheduling, Cryptography, Explainable AI, ...
• Efficient Encodings of Problems into SAT:
  • General Encoding Techniques, CNF Encodings of Constraints, Properties of CNF Encodings, ...
• Practical Hardness of SAT:
  • Tractable Classes, Instance Structure, Hardest Instances, Proof Complexity, ...