Boolean satisfiability (SAT) solvers are at the core of efficient approaches for solving a vast
multitude of practical problems. Moreover, albeit targeting an NP-complete problem, SAT …

One of the most important paradigm shifts in the use of SAT solvers for solving industrial
problems has been the introduction of clause learning. Clause learning entails adding a …

Recent advances in program repair techniques have raised the possibility of patching bugs
automatically. For an automatically generated patch to be accepted by developers, it should …

This paper presents open-wbo, a new MaxSAT solver. open-wbo has two main features.
First, it is an open-source solver that can be easily modified and extended. Most MaxSAT …

Recent work proposed a toolkit PySAT aiming at fast and easy prototy** with propositional
satisfiability (SAT) oracles in Python, which enabled one to exploit the power of the original …

Much effort is spent by programmers everyday in trying to reduce long, failing execution
traces to the cause of the error. We present an algorithm for error cause localization based …

Abstract Maximum Satisfiability (MaxSAT) is an optimization version of SAT, and many real
world applications can be naturally encoded as such. Solving MaxSAT is an important …

Core-guided approaches to solving MAXSAT have proved to be effective on industrial
problems. These approaches solve a MAXSAT formula by building a sequence of SAT …

Maxsat is an optimization version of Satisfiability aimed at finding a truth assignment that
maximizes the satisfaction of the theory. The technique of solving a sequence of SAT …

Many industrial optimization problems can be translated to MaxSAT. Although the general
problem is NP hard, like SAT, many practical problems may be solved using modern …