Affiliation:
1. Microsoft Research, Cambridge, UK
2. Microsoft Research, La Avenida Mountain View, CA
Abstract
Propositional Satisfiability (SAT) and Constraint Programming (CP) have developed as two relatively independent threads of research cross-fertilizing occasionally. These two approaches to problem solving have a lot in common as evidenced by similar ideas underlying the branch and prune algorithms that are most successful at solving both kinds of problems. They also exhibit differences in the way they are used to state and solve problems since SAT's approach is, in general, a black-box approach, while CP aims at being tunable and programmable. This survey overviews the two areas in a comparative way, emphasizing the similarities and differences between the two and the points where we feel that one technology can benefit from ideas or experience acquired from the other.
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
59 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An efficient circuit-based SAT solver and its application in logic equivalence checking;Microelectronics Journal;2023-12
2. Fuzzing for CPS Mutation Testing;2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE);2023-09-11
3. Building a Network Knowledge Base Based on a Belief Revision Operator;Computational Science and Its Applications – ICCSA 2023 Workshops;2023
4. Quantaloidal Approach to Constraint Satisfaction;Electronic Proceedings in Theoretical Computer Science;2022-11-03
5. Model Checking Algorithm for Repairing Inference between Conjunctive Forms;Computación y Sistemas;2022-03-30