@inproceedings{e1e4f2b2e67a4e8bbf65ebda0fc3e184,
title = "Seeking practical CDCL insights from theoretical SAT benchmarks",
abstract = "Over the last decades Boolean satisfiability (SAT) solvers based on conflict-driven clause learning (CDCL) have developed to the point where they can handle formulas with millions of variables. Yet a deeper understanding of how these solvers can be so successful has remained elusive. In this work we shed light on CDCL performance by using theoretical benchmarks, which have the attractive features of being a) scalable, b) extremal with respect to different proof search parameters, and c) theoretically easy in the sense of having short proofs in the resolution proof system underlying CDCL. This allows for a systematic study of solver heuristics and how efficiently they search for proofs. We report results from extensive experiments on a wide range of benchmarks. Our findings include several examples where theory predicts and explains CDCL behaviour, but also raise a number of intriguing questions for further study.",
author = "Jan Elffers and Cru, {Jes{\'u}s Gir{\'a}ldez} and Stephan Gocht and Jakob Nordstr{\"o}m and Laurent Simon",
year = "2018",
doi = "10.24963/ijcai.2018/181",
language = "English",
series = "IJCAI International Joint Conference on Artificial Intelligence",
publisher = "International Joint Conferences on Artificial Intelligence",
pages = "1300--1308",
editor = "Jerome Lang",
booktitle = "Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018",
note = "27th International Joint Conference on Artificial Intelligence, IJCAI 2018 ; Conference date: 13-07-2018 Through 19-07-2018",
}