{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:32:24Z","timestamp":1772119944035,"version":"3.50.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Innovations Syst Softw Eng"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s11334-024-00589-8","type":"journal-article","created":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T16:02:08Z","timestamp":1729526528000},"page":"1009-1024","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["ARIA-QA: AI-agent based requirements inspection and analysis through question answering"],"prefix":"10.1007","volume":"21","author":[{"given":"Chitrak","family":"Biswas","sequence":"first","affiliation":[]},{"given":"Souvick","family":"Das","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,21]]},"reference":[{"key":"589_CR1","doi-asserted-by":"publisher","unstructured":"Abualhaija S, Arora C, Sleimi A, Briand LC (2022) Automated question answering for improved understanding of compliance requirements: A multi-document study. In: 2022 IEEE 30th International Requirements Engineering Conference (RE). pp. 39\u201350. https:\/\/doi.org\/10.1109\/RE54965.2022.00011","DOI":"10.1109\/RE54965.2022.00011"},{"issue":"11","key":"589_CR2","doi-asserted-by":"publisher","first-page":"4647","DOI":"10.1109\/TSE.2021.3124332","volume":"48","author":"O Amaral","year":"2021","unstructured":"Amaral O, Abualhaija S, Torre D, Sabetzadeh M, Briand LC (2021) Ai-enabled automation for completeness checking of privacy policies. IEEE Trans Software Eng 48(11):4647\u20134674","journal-title":"IEEE Trans Software Eng"},{"key":"589_CR3","unstructured":"Anthropic A (2024) The claude 3 model family: Opus, sonnet, haiku. Claude-3 Model Card"},{"key":"589_CR4","doi-asserted-by":"publisher","first-page":"2509","DOI":"10.1007\/s10664-019-09693-x","volume":"24","author":"C Arora","year":"2019","unstructured":"Arora C, Sabetzadeh M, Briand LC (2019) An empirical study on the potential usefulness of domain models for completeness checking of requirements. Empir Softw Eng 24:2509\u20132539","journal-title":"Empir Softw Eng"},{"key":"589_CR5","doi-asserted-by":"crossref","unstructured":"Chen J, Xiao S, Zhang P, Luo K, Lian D, Liu Z (2024) Bge m3-embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation. arXiv preprint arXiv:2402.03216","DOI":"10.18653\/v1\/2024.findings-acl.137"},{"key":"589_CR6","doi-asserted-by":"crossref","unstructured":"Dalpiaz F, Van\u00a0der Schalk I, Lucassen G (2018) Pinpointing ambiguity and incompleteness in requirements engineering via information visualization and nlp. In: Requirements Engineering: Foundation for Software Quality: 24th International Working Conference, REFSQ 2018, Utrecht, The Netherlands, March 19-22, 2018, Proceedings 24. pp. 119\u2013135. Springer","DOI":"10.1007\/978-3-319-77243-1_8"},{"key":"589_CR7","doi-asserted-by":"crossref","unstructured":"Es S, James J, Espinosa-Anke L, Schockaert S (2023) Ragas: Automated evaluation of retrieval augmented generation. arXiv preprint arXiv:2309.15217","DOI":"10.18653\/v1\/2024.eacl-demo.16"},{"key":"589_CR8","doi-asserted-by":"crossref","unstructured":"Ezzini S, Abualhaija S, Arora C, Sabetzadeh M (2023) Ai-based question answering assistance for analyzing natural-language requirements. arXiv preprint arXiv:2302.04793","DOI":"10.1109\/ICSE48619.2023.00113"},{"key":"589_CR9","doi-asserted-by":"crossref","unstructured":"Ezzini S, Abualhaija S, Arora C, Sabetzadeh M, Briand LC (2021) Using domain-specific corpora for improved handling of ambiguity in requirements. In: 2021 IEEE\/ACM 43rd International Conference on Software Engineering (ICSE). pp. 1485\u20131497. IEEE","DOI":"10.1109\/ICSE43902.2021.00133"},{"issue":"3","key":"589_CR10","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1007\/s10515-019-00261-7","volume":"26","author":"A Ferrari","year":"2019","unstructured":"Ferrari A, Esuli A (2019) An nlp approach for cross-domain ambiguity detection in requirements engineering. Autom Softw Eng 26(3):559\u2013598","journal-title":"Autom Softw Eng"},{"key":"589_CR11","doi-asserted-by":"crossref","unstructured":"Ferrari A, Spagnolo GO, Gnesi S (2017) Pure: A dataset of public requirements documents. In: 2017 IEEE 25th International Requirements Engineering Conference (RE). pp. 502\u2013505. IEEE","DOI":"10.1109\/RE.2017.29"},{"issue":"6","key":"589_CR12","doi-asserted-by":"publisher","first-page":"3972","DOI":"10.1007\/s10664-019-09718-5","volume":"24","author":"I Hadar","year":"2019","unstructured":"Hadar I, Zamansky A, Berry DM (2019) The inconsistency between theory and practice in managing inconsistency in requirements engineering. Empir Softw Eng 24(6):3972\u20134005","journal-title":"Empir Softw Eng"},{"key":"589_CR13","unstructured":"J\u00e9gou H, Douze M, Johnson J, Hosseini L, Deng C (2022) Faiss: Similarity search and clustering of dense vectors library. Astrophysics Source Code Library pp. ascl\u20132210"},{"key":"589_CR14","unstructured":"Jiang AQ, Sablayrolles A, Roux A, Mensch A, Savary B, Bamford C, Chaplot DS, Casas Ddl, Hanna EB, Bressand F, et\u00a0al (2024) Mixtral of experts. arXiv preprint arXiv:2401.04088"},{"key":"589_CR15","unstructured":"Kevian D, Syed U, Guo X, Havens A, Dullerud G, Seiler P, Qin L, Hu B (2024) Capabilities of large language models in control engineering: A benchmark study on gpt-4, claude 3 opus, and gemini 1.0 ultra. arXiv preprint arXiv:2404.03647"},{"key":"589_CR16","unstructured":"Lamsweerde Av (2009) Requirements engineering: from system goals to UML models to software specifications. John Wiley & Sons, Ltd"},{"key":"589_CR17","first-page":"9459","volume":"33","author":"Retrieval-augmented generation for knowledge-intensive nlp tasks","year":"2020","unstructured":"Retrieval-augmented generation for knowledge-intensive nlp tasks (2020) Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., K\u00fcttler, H., Lewis, M., Yih, W.t., Rockt\u00e4schel, T., et al. Adv Neural Inf Process Syst 33:9459\u20139474","journal-title":"Adv Neural Inf Process Syst"},{"key":"589_CR18","unstructured":"Lin CY (2004) Rouge: A package for automatic evaluation of summaries. In: Text summarization branches out. pp. 74\u201381"},{"key":"589_CR19","doi-asserted-by":"crossref","unstructured":"Luitel D, Hassani S, Sabetzadeh M (2023) Using language models for enhancing the completeness of natural-language requirements. In: International Working Conference on Requirements Engineering: Foundation for Software Quality. pp. 87\u2013104. Springer","DOI":"10.1007\/978-3-031-29786-1_7"},{"key":"589_CR20","doi-asserted-by":"crossref","unstructured":"Muennighoff N, Tazi N, Magne L, Reimers N (2022) Mteb: Massive text embedding benchmark. arXiv preprint arXiv:2210.07316","DOI":"10.18653\/v1\/2023.eacl-main.148"},{"key":"589_CR21","unstructured":"Nogueira R, Yang W, Cho K, Lin J (2019) Multi-stage document ranking with bert. arXiv preprint arXiv:1910.14424"},{"key":"589_CR22","unstructured":"OpenAI: Gpt-4 technical report. In: GPT-4 Technical Report (2023)"},{"key":"589_CR23","unstructured":"Ouyang L, Wu J, Jiang X, Almeida D, Wainwright C, Mishkin P, Zhang C, Agarwal S, Slama K, Ray A et al (2022) Training language models to follow instructions with human feedback. Adv Neural Inf Process Syst 35:27730\u201327744"},{"key":"589_CR24","doi-asserted-by":"crossref","unstructured":"Papineni K, Roukos S, Ward T, Zhu WJ (2002) Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics. pp. 311\u2013318","DOI":"10.3115\/1073083.1073135"},{"key":"589_CR25","unstructured":"Parnami A, Lee M (2022) Learning from few examples: A summary of approaches to few-shot learning. arXiv preprint arXiv:2203.04291"},{"key":"589_CR26","doi-asserted-by":"crossref","unstructured":"Platzer C, Dustdar S (2005) A vector space search engine for web services. In: Third European Conference on Web Services (ECOWS\u201905). pp. 9\u2013pp. IEEE","DOI":"10.1109\/ECOWS.2005.5"},{"key":"589_CR27","unstructured":"Romera-Paredes B, Torr P (2015) An embarrassingly simple approach to zero-shot learning. In: International conference on machine learning. pp. 2152\u20132161. PMLR"},{"issue":"1\u20136","key":"589_CR28","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/S1389-1286(00)00046-3","volume":"33","author":"R Stata","year":"2000","unstructured":"Stata R, Bharat K, Maghoul F (2000) The term vector database: fast access to indexing terms for web pages. Comput Netw 33(1\u20136):247\u2013255","journal-title":"Comput Netw"},{"key":"589_CR29","unstructured":"Thoppilan R, De\u00a0Freitas D, Hall J, Shazeer N, Kulshreshtha A, Cheng HT, Jin A, Bos T, Baker L, Du Y, et\u00a0al (2022) Lamda: Language models for dialog applications. arXiv preprint arXiv:2201.08239"},{"key":"589_CR30","unstructured":"Touvron H, Martin L, Stone K, Albert P, Almahairi A, Babaei Y, Bashlykov N, Batra S, Bhargava P, Bhosale S, et\u00a0al (2023) Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288"},{"key":"589_CR31","doi-asserted-by":"crossref","unstructured":"Van\u00a0Lamsweerde A (2000) Requirements engineering in the year 00: A research perspective. In: Proceedings of the 22nd international conference on Software engineering. pp. 5\u201319","DOI":"10.1145\/337180.337184"},{"key":"589_CR32","unstructured":"Wang A, Pruksachatkun Y, Nangia N, Singh A, Michael J, Hill F, Levy O, Bowman S (2019) Superglue: A stickier benchmark for general-purpose language understanding systems. Adv Neural Inf Process Syst 32"},{"key":"589_CR33","doi-asserted-by":"crossref","unstructured":"Wang W, Zheng VW, Yu H, Miao C (2019) A survey of zero-shot learning: Settings, methods, and applications. ACM Trans Intell Syst Technol (TIST) 10(2):1\u201337","DOI":"10.1145\/3293318"},{"key":"589_CR34","doi-asserted-by":"crossref","unstructured":"Zhao L, Alhoshan W, Ferrari A, Letsholo KJ, Ajagbe MA, Chioasca EV, Batista-Navarro RT (2021) Natural language processing for requirements engineering: A systematic mapping study. ACM Comput Surv (CSUR) 54(3):1\u201341","DOI":"10.1145\/3444689"},{"key":"589_CR35","unstructured":"Zheng L, Chiang WL, Sheng Y, Zhuang S, Wu Z, Zhuang Y, Lin Z, Li Z, Li D, Xing E, et\u00a0al (2024) Judging llm-as-a-judge with mt-bench and chatbot arena. Adv Neural Inf Process Syst 36"}],"container-title":["Innovations in Systems and Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11334-024-00589-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11334-024-00589-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11334-024-00589-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T00:16:09Z","timestamp":1757117769000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11334-024-00589-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,21]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["589"],"URL":"https:\/\/doi.org\/10.1007\/s11334-024-00589-8","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-4399368\/v1","asserted-by":"object"}]},"ISSN":["1614-5046","1614-5054"],"issn-type":[{"value":"1614-5046","type":"print"},{"value":"1614-5054","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,21]]},"assertion":[{"value":"10 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}