Validating SAT solvers using an independent resolution-based checker: practical implementations and other applications
By Lintao Zhang, Sharad Malik. 2003 Design, Automation and Test in Europe Conference and Exhibition, 2003
339 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Software
View Paper: https://www.semanticscholar.org/paper/94670dc7e573d718027f8cfe6192990f5d57684a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Benjamin Kaufmann
- Torsten Schaub
- Martin Gebser
- António Morgado
- Joao Marques-Silva
- Armin Biere
- Zhaohui Fu
- Kenneth L. McMillan
In Computational Theory and Mathematics
- Armin Biere
- Joao Marques-Silva
- António Morgado
- Torsten Schaub
- Martin Gebser
- Benjamin Kaufmann
- Kenneth L. McMillan
- Zhaohui Fu
In Software
- Armin Biere
- Torsten Schaub
- Martin Gebser
- Benjamin Kaufmann
- Zhaohui Fu
- Joao Marques-Silva
- António Morgado
- Kenneth L. McMillan
Citations in the corpus
- Conflict-driven answer set solving: From theory to practice (2012, methodology): “[128,115]) also apply to CDNL-ASP, given that both search procedures make use of conflict-driven assertions to exclude repetitions of assignments.”
- Interpolation and SAT-Based Model Checking (2003, background): “In the unsatisfiable case, it can produce a proof of unsatisfiability [16, 25 ].”
- Iterative and core-guided MaxSAT solving: A survey and assessment (2013, background): “of the information provided by unsatisf iable cores [128] to guide the search.”
- On Solving the Partial MAX-SAT Problem (2006, methodology): “the UNSAT core [21], and uses relaxation variables to eliminate these UNSAT cores one by one until the instance becomes satisfiable.”
- PicoSAT Essentials (2008, background): “Another important feature of modern SAT solvers is their ability to produce proof traces [40, 18, 13, 36, 22, 16].”