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 …

Given a loop-free sequence of instructions, superoptimization techniques use a constraint
solver to search for an equivalent sequence that is optimal for a desired objective. The …

Boolean Satisfiability (SAT) is arguably the archetypical NP-complete decision problem.
Progress in SAT solving algorithms has motivated an ever increasing number of practical …

There are well known cases of Quantified Boolean Formulas (QBFs) that have short winning
strategies (Skolem/Herbrand functions) but that are hard to solve by nowadays solvers. This …

Abstract Machine learning (ML) is ubiquitous in modern life. Since it is being deployed in
technologies that affect our privacy and safety, it is often crucial to understand the reasoning …

Symmetry breaking is a crucial technique to solve many graph problems. However, current
state-of-the-art techniques break graph symmetries only partially, causing search algorithms …

Prime compilation aims to generate all prime implicates/implicants of a Boolean formula.
Recently, prime compilation of non-clausal formulae has received great attention. Since it is …

Self-Explainable Graph Neural Networks (SE-GNNs) are popular explainable-by-design
GNNs, but the properties and the limitations of their explanations are not well understood …

The object of this study is models of low-power digital logic circuits. The problem being
solved is the effectiveness of the technique for simplifying Boolean functions to obtain …

In this paper, we will show how to handle a new normal form called terse normal form (TNF),
which is crucial to the development of a novel tableau method that solves realizability and …