{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T02:42:30Z","timestamp":1775011350669,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819688883","type":"print"},{"value":"9789819688890","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"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":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-96-8889-0_37","type":"book-chapter","created":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T08:57:47Z","timestamp":1751273867000},"page":"432-443","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LLM-Based MaSE, A Software Development Framework for\u00a0Developing Multi-agent Systems"],"prefix":"10.1007","author":[{"given":"Sahar","family":"Hajjarzadeh","sequence":"first","affiliation":[]},{"given":"Zahra","family":"Shakeri Hossein Abad","sequence":"additional","affiliation":[]},{"given":"Behrouz","family":"Far","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"37_CR1","unstructured":"Zhang, Q., et al.: A Survey on Large Language Models for Software Engineering (2023). http:\/\/arxiv.org\/abs\/2312.15223"},{"key":"37_CR2","doi-asserted-by":"publisher","first-page":"82434","DOI":"10.1109\/ACCESS.2022.3196347","volume":"10","author":"E Dehaerne","year":"2022","unstructured":"Dehaerne, E., Dey, B., Halder, S., De Gendt, S., Meert, W.: Code generation using machine learning: a systematic review. IEEE Access 10, 82434\u201382455 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3196347","journal-title":"IEEE Access"},{"key":"37_CR3","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/MS.2023.3248401","volume":"40","author":"I Ozkaya","year":"2023","unstructured":"Ozkaya, I.: Application of large language models to software engineering tasks: opportunities, risks, and implications. IEEE Softw. 40, 4\u20138 (2023). https:\/\/doi.org\/10.1109\/MS.2023.3248401","journal-title":"IEEE Softw."},{"key":"37_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3695988","volume":"33","author":"X Hou","year":"2024","unstructured":"Hou, X., et al.: Large language models for software engineering: a systematic literature review. ACM Trans. Softw. Eng. Methodol. 33, 1\u201379 (2024). https:\/\/doi.org\/10.1145\/3695988","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"key":"37_CR5","doi-asserted-by":"publisher","unstructured":"Fan, A., et al.: Large language models for software engineering: survey and open problems. In: 2023 IEEE\/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE), pp. 31\u201353. IEEE, Melbourne, Australia (2023). https:\/\/doi.org\/10.1109\/ICSE-FoSE59343.2023.00008","DOI":"10.1109\/ICSE-FoSE59343.2023.00008"},{"key":"37_CR6","doi-asserted-by":"publisher","unstructured":"Chang, T., Chen, S., Fan, G., Feng, Z.: A Self-iteration code generation method based on large language models. In: 2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS), pp. 275\u2013281 (2023). https:\/\/doi.org\/10.1109\/ICPADS60453.2023.00049","DOI":"10.1109\/ICPADS60453.2023.00049"},{"key":"37_CR7","doi-asserted-by":"publisher","unstructured":"DeLoach, S.A.: The MaSE methodology. In: Bergenti, F., Gleizes, M.-P., and Zambonelli, F. (eds.) Methodologies and Software Engineering for Agent Systems, pp. 107\u2013125. Kluwer Academic Publishers, Boston (2004). https:\/\/doi.org\/10.1007\/1-4020-8058-1_8","DOI":"10.1007\/1-4020-8058-1_8"},{"key":"37_CR8","unstructured":"Shin, J., Tang, C., Mohati, T., Nayebi, M., Wang, S., Hemmati, H.: Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks (2023). http:\/\/arxiv.org\/abs\/2310.10508"},{"key":"37_CR9","doi-asserted-by":"publisher","unstructured":"Fried, D., et al.: InCoder: A Generative Model for Code Infilling and Synthesis (2023). http:\/\/arxiv.org\/abs\/2204.05999, https:\/\/doi.org\/10.48550\/arXiv.2204.05999","DOI":"10.48550\/arXiv.2204.05999"},{"key":"37_CR10","doi-asserted-by":"publisher","unstructured":"Chen, M., et al.: Evaluating Large Language Models Trained on Code (2021). http:\/\/arxiv.org\/abs\/2107.03374, https:\/\/doi.org\/10.48550\/arXiv.2107.03374","DOI":"10.48550\/arXiv.2107.03374"},{"key":"37_CR11","doi-asserted-by":"publisher","unstructured":"Rozi\u00e8re, B., et al.: Code Llama: Open Foundation Models for Code (2024). http:\/\/arxiv.org\/abs\/2308.12950, https:\/\/doi.org\/10.48550\/arXiv.2308.12950","DOI":"10.48550\/arXiv.2308.12950"},{"key":"37_CR12","doi-asserted-by":"publisher","unstructured":"Gunasekar, S., et al.: Textbooks Are All You Need (2023). http:\/\/arxiv.org\/abs\/2306.11644, https:\/\/doi.org\/10.48550\/arXiv.2306.11644","DOI":"10.48550\/arXiv.2306.11644"},{"key":"37_CR13","doi-asserted-by":"publisher","unstructured":"Li, Y., et al.: Competition-level code generation with AlphaCode. Science 378, 1092\u20131097 (2022). https:\/\/doi.org\/10.1126\/science.abq1158","DOI":"10.1126\/science.abq1158"},{"key":"37_CR14","doi-asserted-by":"publisher","unstructured":"Jiang, X., et al.: Self-planning code generation with large language models. ACM Trans. Softw. Eng. Methodol. 33, 182:1\u2013182:30 (2024). https:\/\/doi.org\/10.1145\/3672456","DOI":"10.1145\/3672456"},{"key":"37_CR15","doi-asserted-by":"publisher","unstructured":"Vallecillos Ruiz, F.: Agent-driven automatic software improvement. In: Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering, pp. 470\u2013475. Association for Computing Machinery, New York, NY, USA (2024). https:\/\/doi.org\/10.1145\/3661167.3661171","DOI":"10.1145\/3661167.3661171"},{"key":"37_CR16","doi-asserted-by":"publisher","unstructured":"Tang, X., et al.: CodeAgent: autonomous communicative agents for code review. In: Al-Onaizan, Y., Bansal, M., and Chen, Y.-N. (eds.) Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 11279\u201311313. Association for Computational Linguistics, Miami, Florida, USA (2024). https:\/\/doi.org\/10.18653\/v1\/2024.emnlp-main.632","DOI":"10.18653\/v1\/2024.emnlp-main.632"},{"key":"37_CR17","doi-asserted-by":"publisher","unstructured":"Rasheed, Z., et al.: CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology (2024). http:\/\/arxiv.org\/abs\/2402.01411, https:\/\/doi.org\/10.48550\/arXiv.2402.01411","DOI":"10.48550\/arXiv.2402.01411"},{"key":"37_CR18","doi-asserted-by":"publisher","unstructured":"Sami, M.A., Waseem, M., Rasheed, Z., Saari, M., Syst\u00e4, K., Abrahamsson, P.: Experimenting with Multi-Agent Software Development: Towards a Unified Platform (2024). http:\/\/arxiv.org\/abs\/2406.05381, https:\/\/doi.org\/10.48550\/arXiv.2406.05381","DOI":"10.48550\/arXiv.2406.05381"},{"key":"37_CR19","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/s11528-023-00896-0","volume":"68","author":"W Cain","year":"2024","unstructured":"Cain, W.: Prompting change: exploring prompt engineering in large language model AI and its potential to transform education. TechTrends 68, 47\u201357 (2024). https:\/\/doi.org\/10.1007\/s11528-023-00896-0","journal-title":"TechTrends"},{"key":"37_CR20","doi-asserted-by":"publisher","unstructured":"Marvin, G., Hellen, N., Jjingo, D., Nakatumba-Nabende, J.: Prompt engineering in large language models. In: Jacob, I.J., Piramuthu, S., and Falkowski-Gilski, P. (eds.) Data Intelligence and Cognitive Informatics. ICDICI 2023. Algorithms for Intelligent Systems, pp. 387\u2013402. Springer Nature, Singapore (2024). https:\/\/doi.org\/10.1007\/978-981-99-7962-2_30","DOI":"10.1007\/978-981-99-7962-2_30"},{"key":"37_CR21","doi-asserted-by":"publisher","unstructured":"Vatsal, S., Dubey, H.: A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks (2024). http:\/\/arxiv.org\/abs\/2407.12994, https:\/\/doi.org\/10.48550\/arXiv.2407.12994","DOI":"10.48550\/arXiv.2407.12994"},{"key":"37_CR22","unstructured":"Chen, B., Zhang, Z., Langren\u00e9, N., Zhu, S.: Unleashing the potential of prompt engineering in large language models: a comprehensive review (2024). http:\/\/arxiv.org\/abs\/2310.14735"},{"key":"37_CR23","doi-asserted-by":"publisher","unstructured":"White, J., et al.: A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT (2023). http:\/\/arxiv.org\/abs\/2302.11382, https:\/\/doi.org\/10.48550\/arXiv.2302.11382","DOI":"10.48550\/arXiv.2302.11382"},{"key":"37_CR24","doi-asserted-by":"publisher","unstructured":"White, J., Hays, S., Fu, Q., Spencer-Smith, J., Schmidt, D.C.: ChatGPT prompt patterns for improving code quality, refactoring, requirements elicitation, and software design. In: Nguyen-Duc, A., Abrahamsson, P., Khomh, F. (eds.) Generative AI for Effective Software Development, pp. 71\u2013108. Springer Nature Switzerland, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-55642-5_4","DOI":"10.1007\/978-3-031-55642-5_4"},{"key":"37_CR25","doi-asserted-by":"publisher","unstructured":"Gu, X., et al.: On the effectiveness of large language models in domain-specific code generation. ACM Trans. Softw. Eng. Methodol. 3697012 (2024). https:\/\/doi.org\/10.1145\/3697012","DOI":"10.1145\/3697012"},{"key":"37_CR26","doi-asserted-by":"publisher","unstructured":"Wohlin, C., Runeson, P., H\u00f6st, M., Ohlsson, M.C., Regnell, B., Wessl\u00e9n, A.: Experimentation in Software Engineering. Springer, Berlin, Heidelberg (2024). https:\/\/doi.org\/10.1007\/978-3-662-69306-3","DOI":"10.1007\/978-3-662-69306-3"}],"container-title":["Lecture Notes in Computer Science","Advances and Trends in Artificial Intelligence. Theory and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-8889-0_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T01:34:08Z","timestamp":1775007248000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-8889-0_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,1]]},"ISBN":["9789819688883","9789819688890"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-8889-0_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,1]]},"assertion":[{"value":"1 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"IEA\/AIE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kytakyushu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"38","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ieaaie2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.i-somet.org\/iea-aie2025\/committees.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}