What Is Programming? And How To Get Started
January 28, 2025
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(43 reviews)
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In this course, you will learn how to apply satisfiability (SAT/SMT) tools to solve a wide range of problems.
Several basic examples are given to get the flavour of the applications: fitting rectangles to be applied for printing posters, scheduling problems, solving puzzles, and program correctness. Also, the underlying theory is presented: resolution as a basic approach for propositional satisfiability, the CDCL framework to scale up for big formulas, and the simplex method to deal with linear inequalities. The lightweight approach to following the Automated Reasoning: satisfiability course is just watching the lectures and doing the corresponding quizzes. To get a flavor of the topic this may work out fine. However, the much more interesting approach is to use this as a basis to apply SAT/SMT yourself on several problems, for instance on the problems presented in the honor's assignment.
This module introduces SAT (satisfiability) and SMT (SAT modulo theories) from scratch, and gives a number of examples of how to apply SAT.
6 videos2 readings3 assignments
This module shows a number of applications of satisfiability modulo the theory of linear inequalities (SMT)
4 videos2 readings7 assignments
This module describes how a rule called Resolution serves to determine whether a propositional formula in conjunctive normal form (CNF) is unsatisfiable. It is shown how an approach called DPLL does the same job, and how it is related to resolution. Finally, it is shown how current SAT solvers essentially implement and optimize DPLL.
6 videos5 assignments
This module consists of two parts. The first part is about transforming arbitrary propositional formulas to CNF, leading to the Tseitin transformation doing this job such that the size of the transformed formula is linear in the size of the original formula. The second part is about extending SAT to SMT, in particular to dealing with linear inequalities. It is shown how the Simplex method for linear optimization serves for this job; the Simplex method itself is explained in detail.
6 videos4 assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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University of Glasgow
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Birla Institute of Technology & Science, Pilani
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University of Washington
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Reviewed on Jan 7, 2023
The course is very good. You can learn a lot.
The only downsido is that the questions on some quizzes are not very clear. Like how do you cont the number of steps required to end a DPLL prove etc.
Reviewed on May 26, 2024
This course really opened my mind on the possibilities that can be achieved with the SMT solver. Great course!!!
Reviewed on Aug 16, 2019
Good course, but some quizes are a bit confusing :)Thank you very much professor.
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