SAT or Satisfiability type problem is the problem of determining if there exists a solution to a boolean formula. It checks if a combination of true/False values exist that evaluated the given boolean expression to true.

The representation of a boolean formula is expressed in Conjuctive Normal Form.

The problem’s complexity can be broadly classifed as Unrestricted and restricted or SAT-3. The key difference being that the element may be present any number of time in a conjuctive clause in Unrestricted form and exactly once in a restricted form.


It was the first problem that was proved to be NP-complete. Till date there exists no known algorithm that solves every given SAT problem in a polynominal problem.

The wide areas of SAT solving are artificial intelligence, circuit design and Automatic theorem proving.

Recently Urmila Mahadev theoretically formalized the long standing question of Quantum computation, How to know whether anything Quantum has happened ?. In her method she has reduced the complex problem to SAT-3 instance problems.


The most common algorithm is called DPLL algorithm that works as a conflict-driven learning algorithm. The other popular but randomized algorithm is called PPSZ aLgorithm.

  • DPLL Algorithm
    • It involves performing a DFS through space of possible assignments for conjuctive sets and stops if statifiability is found or all options have been tested.
    • Optimizations can be performed by skipping the branches where no satisfying assignments occur and looking for the maximum ‘search space’ .
    • Conflict analysis is done and those clauses that are not rooted are removed or are not searched.


There has been quite a few Coq formalization done that can be looked up. Here I am sharing onw done by Prof. Adam Chlipala as a part of his course Interactive Theorem Proving link.

Over the years Proof-assistant based SMT-SAT solvers have been researched upon. example : Z3 Theorem prover , SMT coq.