{"day":"11","publisher":"Springer Nature","publication":"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)","oa_version":"Published Version","doi":"10.1007/978-3-031-71162-6_31","department":[{"_id":"KrCh"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2024-10-01T09:56:54Z","date_created":"2024-09-29T22:01:37Z","project":[{"grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E"}],"intvolume":"     14933","alternative_title":["LNCS"],"acknowledgement":"This work was supported in part by the ERC-2020-CoG 863818 (FoRM-SMArt) and the Hong Kong Research Grants Council ECS Project Number 26208122.","ddc":["000"],"type":"conference","oa":1,"page":"600-619","conference":{"start_date":"2024-09-09","end_date":"2024-09-13","location":"Milan, Italy","name":"FM: Formal Methods"},"volume":14933,"publication_identifier":{"issn":["0302-9743"],"isbn":["9783031711619"],"eissn":["1611-3349"]},"file":[{"success":1,"relation":"main_file","access_level":"open_access","date_updated":"2024-10-01T09:56:54Z","file_id":"18165","creator":"dernst","content_type":"application/pdf","file_name":"2024_LNCS_Chatterjee.pdf","checksum":"223845be9e754681ee218866827c95e7","file_size":650495,"date_created":"2024-10-01T09:56:54Z"}],"has_accepted_license":"1","quality_controlled":"1","language":[{"iso":"eng"}],"author":[{"first_name":"Krishnendu","last_name":"Chatterjee","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"id":"391365CE-F248-11E8-B48F-1D18A9856A87","full_name":"Goharshady, Amir Kafshdar","orcid":"0000-0003-1702-6584","last_name":"Goharshady","first_name":"Amir Kafshdar"},{"first_name":"Ehsan","last_name":"Goharshady","full_name":"Goharshady, Ehsan"},{"full_name":"Karrabi, Mehrdad","id":"67638922-f394-11eb-9cf6-f20423e08757","first_name":"Mehrdad","last_name":"Karrabi"},{"first_name":"Dorde","last_name":"Zikelic","orcid":"0000-0002-4681-1699","full_name":"Zikelic, Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87"}],"citation":{"short":"K. Chatterjee, A.K. Goharshady, E. Goharshady, M. Karrabi, D. Zikelic, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, 2024, pp. 600–619.","chicago":"Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Ehsan Goharshady, Mehrdad Karrabi, and Dorde Zikelic. “Sound and Complete Witnesses for Template-Based Verification of LTL Properties on Polynomial Programs.” In <i>Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>, 14933:600–619. Springer Nature, 2024. <a href=\"https://doi.org/10.1007/978-3-031-71162-6_31\">https://doi.org/10.1007/978-3-031-71162-6_31</a>.","ama":"Chatterjee K, Goharshady AK, Goharshady E, Karrabi M, Zikelic D. Sound and complete witnesses for template-based verification of LTL properties on polynomial programs. In: <i>Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>. Vol 14933. Springer Nature; 2024:600-619. doi:<a href=\"https://doi.org/10.1007/978-3-031-71162-6_31\">10.1007/978-3-031-71162-6_31</a>","apa":"Chatterjee, K., Goharshady, A. K., Goharshady, E., Karrabi, M., &#38; Zikelic, D. (2024). Sound and complete witnesses for template-based verification of LTL properties on polynomial programs. In <i>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i> (Vol. 14933, pp. 600–619). Milan, Italy: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-71162-6_31\">https://doi.org/10.1007/978-3-031-71162-6_31</a>","mla":"Chatterjee, Krishnendu, et al. “Sound and Complete Witnesses for Template-Based Verification of LTL Properties on Polynomial Programs.” <i>Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>, vol. 14933, Springer Nature, 2024, pp. 600–19, doi:<a href=\"https://doi.org/10.1007/978-3-031-71162-6_31\">10.1007/978-3-031-71162-6_31</a>.","ista":"Chatterjee K, Goharshady AK, Goharshady E, Karrabi M, Zikelic D. 2024. Sound and complete witnesses for template-based verification of LTL properties on polynomial programs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). FM: Formal Methods, LNCS, vol. 14933, 600–619.","ieee":"K. Chatterjee, A. K. Goharshady, E. Goharshady, M. Karrabi, and D. Zikelic, “Sound and complete witnesses for template-based verification of LTL properties on polynomial programs,” in <i>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>, Milan, Italy, 2024, vol. 14933, pp. 600–619."},"status":"public","publication_status":"published","date_published":"2024-09-11T00:00:00Z","month":"09","date_updated":"2024-10-01T10:00:23Z","_id":"18155","article_processing_charge":"Yes (in subscription journal)","title":"Sound and complete witnesses for template-based verification of LTL properties on polynomial programs","external_id":{"arxiv":["2403.05386"]},"abstract":[{"text":"We study the classical problem of verifying programs with respect to formal specifications given in the linear temporal logic (LTL). We first present novel sound and complete witnesses for LTL verification over imperative programs. Our witnesses are applicable to both verification (proving) and refutation (finding bugs) settings. We then consider LTL formulas in which atomic propositions can be polynomial constraints and turn our focus to polynomial arithmetic programs, i.e. programs in which every assignment and guard consists only of polynomial expressions. For this setting, we provide an efficient algorithm to automatically synthesize such LTL witnesses. Our synthesis procedure is both sound and semi-complete. Finally, we present experimental results demonstrating the effectiveness of our approach and that it can handle programs which were beyond the reach of previous state-of-the-art tools.","lang":"eng"}],"ec_funded":1,"scopus_import":"1","year":"2024","corr_author":"1","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"}}