{"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/online-set-based-dynamic-analysis-for-sound","title":"Online Set-Based Dynamic Analysis for Sound Predictive Race Detection","arxiv_id":"1907.08337","date":"2019-07-19","proceeding":null,"authors":["Jake Roemer","Michael D. Bond"],"abstract":"Predictive data race detectors find data races that exist in executions other than the observed execution. Smaragdakis et al. introduced the causally-precedes (CP) relation and a polynomial-time analysis for sound (no false races) predictive data race detection. However, their analysis cannot scale beyond analyzing bounded windows of execution traces. This work introduces a novel dynamic analysis called Raptor that computes CP soundly and completely. Raptor is inherently an online analysis that analyzes and finds all CP-races of an execution trace in its entirety. An evaluation of a prototype implementation of Raptor shows that it scales to program executions that the prior CP analysis cannot handle, finding data races that the prior CP analysis cannot find.","url_abs":"http://arxiv.org/abs/1907.08337v1","url_pdf":"http://arxiv.org/pdf/1907.08337v1.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"online-set-based-dynamic-analysis-for-sound","repo_url":"https://github.com/PLaSSticity/Raptor","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}