TL;DR
Here it is explained how and why the WhyUnsat approach is now also directly applicable, at no implementation cost, to IPASIR-UP-based constraint programming by Lazy Clause Generation (LCG) as well as to SAT Modulo Theories (SMT).
This system description reports on how Kissat’s award-winning techniques were adapted to the full-featured incremental SAT solver CaDiCaL, including clausal congruence closure, clausal equivalence sweeping, and bounded variable addition, to support efficient linear proof production with hints.
PalRUP is introduced – an LRUP -based proof format and a bottleneck-free, decentralized parallel checking procedure that only uses the (parallel) file system and is composed of a set of small, sequential trusted components.
This work presents a pipeline that combines LLM-based constraint generation with empirical evaluation and formal verification, and handles MiniZinc’s partial semantics by requiring the base model to be safe and separately proving that the proposed constraint is well-defined for all instances and solutions of the base model.
FLEX is presented, a foundational Constrained Horn Clause (CHC) solver implemented in LEAN, that reduces the trusted base to the kernel alone, and allows using LEAN's entire proof ecosystem to verify low-level systems code, via three contributions.
This work presents the first systematic analysis of how leading LCG solvers maintain their SAT encodings, based on source-code inspection and developer correspondence, and proposes a native CDCL framework for CP, replacing SAT literals with atomic constraints, enabling conflict analysis, nogood learning, and nogood propagation directly at the CP level.
On a new benchmark of 77 problems with an exact oracle, translation to Answer Set Programming is faithful on six of seven domains and fails only on aggregate coverage scheduling, which concentrates the translation tax in one diagnosable pattern.