{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sharpsat-td-in-model-counting-competitions","title":"SharpSAT-TD in Model Counting Competitions 2021-2023","arxiv_id":"2308.15819","date":"2023-08-30","proceeding":null,"authors":["Tuukka Korhonen","Matti Järvisalo"],"abstract":"We describe SharpSAT-TD, our submission to the unweighted and weighted tracks of the Model Counting Competition in 2021-2023, which has won in total $6$ first places in different tracks of the competition. SharpSAT-TD is based on SharpSAT [Thurley, SAT 2006], with the primary novel modification being the use of tree decompositions in the variable selection heuristic as introduced by the authors in [CP 2021]. Unlike the version of SharpSAT-TD evaluated in [CP 2021], the current version that is available in https://github.com/Laakeri/sharpsat-td features also other significant modifications compared to the original SharpSAT, for example, a new preprocessor.","url_abs":"https://arxiv.org/abs/2308.15819v1","url_pdf":"https://arxiv.org/pdf/2308.15819v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sharpsat-td-in-model-counting-competitions","repo_url":"https://github.com/laakeri/sharpsat-td","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"variable-selection","task_name":"Variable Selection"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}