{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T08:56:55Z","timestamp":1767085015362,"version":"3.28.0"},"reference-count":53,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T00:00:00Z","timestamp":1719187200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T00:00:00Z","timestamp":1719187200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,24]]},"DOI":"10.1109\/rew61692.2024.00011","type":"proceedings-article","created":{"date-parts":[[2024,8,21]],"date-time":"2024-08-21T22:51:43Z","timestamp":1724280703000},"page":"46-56","source":"Crossref","is-referenced-by-count":6,"title":["Using GPT-4 Turbo to Automatically Identify Defeaters in Assurance Cases"],"prefix":"10.1109","author":[{"given":"Kimya Khakzad","family":"Shahandashti","sequence":"first","affiliation":[{"name":"York University,Toronto,Ontario,Canada"}]},{"given":"Alvine Boaye","family":"Belle","sequence":"additional","affiliation":[{"name":"York University,Toronto,Ontario,Canada"}]},{"given":"Mohammad Mahdi","family":"Mohajer","sequence":"additional","affiliation":[{"name":"York University,Toronto,Ontario,Canada"}]},{"given":"Oluwafemi","family":"Odu","sequence":"additional","affiliation":[{"name":"York University,Toronto,Ontario,Canada"}]},{"given":"Timothy C.","family":"Lethbridge","sequence":"additional","affiliation":[{"name":"University of Ottawa,Ottawa,Ontario,Canada"}]},{"given":"Hadi","family":"Hemmati","sequence":"additional","affiliation":[{"name":"York University,Toronto,Ontario,Canada"}]},{"given":"Song","family":"Wang","sequence":"additional","affiliation":[{"name":"York University,Toronto,Ontario,Canada"}]}],"member":"263","reference":[{"volume-title":"Lhc mps argument","year":"2023","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119569"},{"journal-title":"Towards developing safety assurance cases for learning-enabled medical cyber-physical systems","year":"2022","author":"Bagheri","key":"ref3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/DSN.2007.29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-NIER58687.2023.00008"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/REW57809.2023.00052"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MODELS58315.2023.00037"},{"volume-title":"Mastering the openai api: Tips and tricks","year":"2023","author":"Dat NGO","key":"ref8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.56094\/jss.v58i1.215"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/SysCon47679.2020.9275852"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ISSREW.2014.89"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s00165-021-00537-4"},{"journal-title":"Foundation, H. Evidence: Using safety cases in industry and healthcare","year":"2012","key":"ref13"},{"journal-title":"Chain of thought prompt tuning in vision language models","year":"2023","author":"Ge","key":"ref14"},{"key":"ref15","article-title":"Eliminative argumentation: A basis for arguing confidence in system properties","author":"GOODENOUGH","year":"2015","journal-title":"SEI, CMU, Pittsburgh, PA, Tech. Rep. CMUISEI-2015-TR-005"},{"journal-title":"Group, T. A. C. W. Goal structuring notation standard version 3","year":"2021","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-08422-0_35"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/HASE.2015.25"},{"journal-title":"The friendly argument notation (fan)","author":"Holloway","key":"ref19"},{"journal-title":"A preliminary evaluation of 11m-based fault localization","year":"2023","author":"Kang","key":"ref20"},{"journal-title":"A prisma-driven systematic mapping study on system assurance weakeners","year":"2023","author":"Khakzad","key":"ref21"},{"key":"ref22","first-page":"22199","article-title":"Large language models are zero-shot reasoners","volume":"35","author":"Kojima","year":"2022","journal-title":"NeuRIPS"},{"key":"ref23","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","volume-title":"NeurIPS","volume":"33","author":"Lewis","year":"2020"},{"journal-title":"Finding failure-inducing test cases with chatgpt","year":"2023","author":"Li","key":"ref24"},{"journal-title":"Understanding llms: A comprehensive overview from training to inference","year":"2024","author":"Liu","key":"ref25"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2019KBP0014"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.11613\/BM.2012.031"},{"issue":"01","key":"ref28","first-page":"1","article-title":"A culturally sensitive test to evaluate nuanced gpt hallucination","volume":"1","author":"MCINTOSH","year":"2023","journal-title":"TAI"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-40923-3_1"},{"journal-title":"Skipanalyzer: An embodied agent for code analysis with large language models","year":"2023","author":"Mohajer","key":"ref30"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/QUATIC.2018.00019"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2022.102781"},{"article-title":"Semantic analysis of assurance cases using s (casp)","volume-title":"GDE Workshop in ICLP (2023)","author":"Murugesan","key":"ref33"},{"journal-title":"A comprehensive overview of large language models","year":"2023","author":"Naveed","key":"ref34"},{"volume-title":"Introducing gpt-4 turbo","year":"2023","key":"ref35"},{"volume-title":"New models and developer prod-ucts announced at devday","year":"14","key":"ref36"},{"volume-title":"Reproducible outputs","year":"2023","key":"ref37"},{"volume-title":"Reproducible outputs openai","year":"2023","key":"ref38"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10061-6_20"},{"volume-title":"Fuzzywuzzy: Fuzzy string matching in python","key":"ref40"},{"key":"ref41","article-title":"Evaluating the effectiveness of gpt-4 turbo in creating defeaters for assurance cases","author":"Shahandashti","year":"2024","journal-title":"Accepted by FORGE"},{"issue":"6","key":"ref42","first-page":"218","article-title":"String matching algorithms and their applicability in various applications","volume":"1","author":"Singla","year":"2012","journal-title":"International journal of soft computing and engineering"},{"journal-title":"Gpt-4 and safety case generation: An exploratory analysis","year":"2023","author":"Sivakumar","key":"ref43"},{"journal-title":"The impact of advanced prompting strategies on the natural language processing capabilities of large language models","year":"2023","author":"Song","key":"ref44"},{"key":"ref45","article-title":"Supporting assurance case development using generative ai","author":"Viger","year":"2023","journal-title":"SAFECOMP 2023"},{"key":"ref46","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"35","author":"Wei","year":"2022","journal-title":"NeuRIPS"},{"key":"ref47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3597503.3639177","article-title":"Demystifying and detecting misuses of deep learning apis","volume-title":"Proceedings of the IEEE\/ACM 46th International Conference on Software Engineering","author":"Wei","year":"2024"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-022-00975-5"},{"journal-title":"Enabling large language models to learn from rules","year":"2023","author":"Yang","key":"ref49"},{"key":"ref50","first-page":"47","article-title":"Auto-matically detecting fallacies in system safety arguments","volume-title":"PRIMA Workshops (2016)","author":"Yuan"},{"journal-title":"Automatic chain of thought prompting in large language models","year":"2022","author":"Zhang","key":"ref51"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICRMS.2018.00045"},{"journal-title":"Large language models can learn rules","year":"2023","author":"Zhu","key":"ref53"}],"event":{"name":"2024 IEEE 32nd International Requirements Engineering Conference Workshops (REW)","start":{"date-parts":[[2024,6,24]]},"location":"Reykjavik, Iceland","end":{"date-parts":[[2024,6,25]]}},"container-title":["2024 IEEE 32nd International Requirements Engineering Conference Workshops (REW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10628444\/10628538\/10628633.pdf?arnumber=10628633","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T05:21:14Z","timestamp":1725340874000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10628633\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,24]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/rew61692.2024.00011","relation":{},"subject":[],"published":{"date-parts":[[2024,6,24]]}}}