@inproceedings{df5ed8d8ca104fe687d3ec30bc3c9a65,
title = "Mining backbone literals in incremental SAT a new kind of incremental data",
abstract = "In incremental SAT solving, information gained from previous similar instances has so far been limited to learned clauses that are still relevant, and heuristic information such as activity weights and scores. In most settings in which incremental satisfiability is applied, many of the instances along the sequence of formulas being solved are unsatisfiable. We show that in such cases, with a P-time analysis of the proof, we can compute a set of literals that are logically implied by the next instance. By adding those literals as assumptions, we accelerate the search.",
author = "Alexander Ivrii and Vadim Ryvchin and Ofer Strichman",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 18th International Conference on Theory and Applications of Satisfiability Testing, SAT 2015 ; Conference date: 24-09-2015 Through 27-09-2015",
year = "2015",
doi = "10.1007/978-3-319-24318-4_8",
language = "الإنجليزيّة",
isbn = "9783319243177",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "88--103",
editor = "Marijn Heule and Sean Weaver",
booktitle = "Theory and Applications of Satisfiability Testing – SAT 2015 - 18th International Conference, Proceedings",
}