{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T19:01:55Z","timestamp":1771614115864,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Recent AI-assisted coding tools, such as GitHub Copilot and Cursor, have enhanced developer productivity through real-time snippet suggestions. However, these tools primarily assist with isolated coding tasks and lack a structured approach to automating complex, multi-step software development workflows. This paper introduces a workflow-centric AI framework for end-to-end automation, from requirements gathering to code generation, validation, and integration, while maintaining developer oversight. Key innovations include automatic context discovery, which selects relevant codebase elements to improve LLM accuracy; a structured execution pipeline using Prompt Pipeline Language (PPL) for iterative code refinement; self-healing mechanisms that generate tests, detect errors, trigger rollbacks, and regenerate faulty code; and AI-assisted code merging, which preserves manual modifications while integrating AI-generated updates. These capabilities enable efficient automation of repetitive tasks, enforcement of coding standards, and streamlined development workflows. This approach lays the groundwork for AI-driven development that remains adaptable as LLM models advance, progressively reducing the need for human intervention while ensuring code reliability.<\/jats:p>","DOI":"10.3390\/computers14030094","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T09:59:17Z","timestamp":1741255157000},"page":"94","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation"],"prefix":"10.3390","volume":"14","author":[{"given":"Vladimir","family":"Sonkin","sequence":"first","affiliation":[{"name":"Luxoft Serbia, 11079 Beograd, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0461-8939","authenticated-orcid":false,"given":"C\u0103t\u0103lin","family":"Tudose","sequence":"additional","affiliation":[{"name":"Luxoft Romania, 020335 Bucharest, Romania"},{"name":"Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"key":"ref_1","unstructured":"(2025, March 01). GitHub Copilot. Available online: https:\/\/github.com\/features\/copilot."},{"key":"ref_2","unstructured":"(2025, March 01). Cursor, the AI Code Editor. Available online: https:\/\/www.cursor.com\/."},{"key":"ref_3","unstructured":"Iusztin, P., and Labonne, M. (2024). LLM Engineer\u2019s Handbook: Master the Art of Engineering Large Language Models from Concept to Production, Packt Publishing."},{"key":"ref_4","unstructured":"Raschka, S. (2024). Build a Large Language Model, Manning."},{"key":"ref_5","unstructured":"Fowler, M. (2018). Refactoring: Improving the Design of Existing Code, Addison-Wesley Professional. [2nd ed.]."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Bonteanu, A.M., Tudose, C., and Anghel, A.M. (2023, January 23\u201325). Multi-Platform Performance Analysis for CRUD Operations in Relational Databases from Java Programs using Spring Data JPA. Proceedings of the 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, Romania.","DOI":"10.1109\/ATEE58038.2023.10108212"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Bonteanu, A.M., Tudose, C., and Anghel, A.M. (2023, January 24). Performance Analysis for CRUD Operations in Relational Databases from Java Programs Using Hibernate. Proceedings of the 2023 24th International Conference on Control Systems and Computer Science (CSCS), Bucharest, Romania.","DOI":"10.1109\/CSCS59211.2023.00109"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Bonteanu, A.M., and Tudose, C. (2024). Performance Analysis and Improvement for CRUD Operations in Relational Databases from Java Programs Using JPA, Hibernate, Spring Data JPA. Appl. Sci., 14.","DOI":"10.20944\/preprints202401.1182.v1"},{"key":"ref_9","unstructured":"Tudose, C. (2023). Java Persistence with Spring Data and Hibernate, Manning."},{"key":"ref_10","unstructured":"Tudose, C. (2020). JUnit in Action, Manning."},{"key":"ref_11","unstructured":"Martin, E. (2023). Mastering SQL Injection: A Comprehensive Guide to Exploiting and Defending Databases, Available online: https:\/\/www.amazon.co.jp\/-\/en\/Evelyn-Martin\/dp\/B0CR8V1TKH."},{"key":"ref_12","unstructured":"Caselli, E., Galluccio, E., and Lombari, G. (2020). SQL Injection Strategies: Practical Techniques to Secure Old Vulnerabilities Against Modern Attacks, Packt Publishing."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Imai, S. (2022, January 22\u201324). Is GitHub Copilot a Substitute for Human Pair-programming?. An Empirical Study. In Proceedings of the ACM\/IEEE 44th International Conference on Software Engineering: Companion Proceedings, Pittsburgh, PA, USA.","DOI":"10.1145\/3510454.3522684"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Nguyen, N., and Nadi, S. (2022, January 22\u201324). An Empirical Evaluation of GitHub Copilot\u2019s Code Suggestions. Proceedings of the 2022 Mining Software Repositories Conference, Pittsburgh, PA, USA.","DOI":"10.1145\/3524842.3528470"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.1142\/S0218194023410048","article-title":"Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot","volume":"33","author":"Zhang","year":"2023","journal-title":"Int. J. Softw. Eng. Knowl. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yetistiren, B., Ozsoy, I., and Tuzun, E. (2022, January 17). Assessing the Quality of GitHub Copilot\u2019s Code Generation. Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering, Singapore.","DOI":"10.1145\/3558489.3559072"},{"key":"ref_17","unstructured":"Suciu, G., Sachian, M.A., Bratulescu, R., Koci, K., and Parangoni, G. (August, January 30). Entity Recognition on Border Security. Proceedings of the 19th International Conference on Availability, Reliability and Security, Vienna, Austria."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"442","DOI":"10.34133\/research.0442","article-title":"Nature-Inspired Intelligent Computing: A Comprehensive Survey","volume":"7","author":"Jiao","year":"2024","journal-title":"Research"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"El Haji, K., Brandt, C., and Zaidman, A. (2024, January 15\u201316). Using GitHub Copilot for Test Generation in Python: An Empirical Study. Proceedings of the 2024 IEEE\/ACM International Conference on Automation of Software Test, Lisbon, Portugal.","DOI":"10.1145\/3644032.3644443"},{"key":"ref_20","unstructured":"Tufano, M., Agarwal, A., Jang, J., Moghaddam, R.Z., and Sundaresan, N. (2024). AutoDev: Automated AI-Driven Development. arXiv."},{"key":"ref_21","unstructured":"Ridnik, T., Kredo, D., and Friedman, I. (2024). Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering. arXiv."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Alenezi, M., and Akour, M. (2025). AI-Driven Innovations in Software Engineering: A Review of Current Practices and Future Directions. Appl. Sci., 15.","DOI":"10.3390\/app15031344"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Babashahi, L., Barbosa, C.E., Lima, Y., Lyra, A., Salazar, H., Arg\u00f4lo, M., de Almeida, M.A., and de Souza, J.M. (2024). AI in the Workplace: A Systematic Review of Skill Transformation in the Industry. Adm. Sci., 14.","DOI":"10.3390\/admsci14060127"},{"key":"ref_24","first-page":"4","article-title":"The Next Frontier in Software Development: AI-Augmented Software Development Processes","volume":"40","author":"Ozkaya","year":"2023","journal-title":"IEEE Softw."},{"key":"ref_25","unstructured":"(2025, March 01). Chatbot App. Available online: https:\/\/chatbotapp.ai."},{"key":"ref_26","unstructured":"(2025, March 01). Using OpenAI o1 Models and GPT-4o Models on ChatGPT. Available online: https:\/\/help.openai.com\/en\/articles\/9824965-using-openai-o1-models-and-gpt-4o-models-on-chatgpt."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Varanasi, B. (2019). Introducing Maven: A Build Tool for Today\u2019s Java Developers, Apress.","DOI":"10.1007\/978-1-4842-5410-3"},{"key":"ref_28","unstructured":"Sommerville, I. (2015). Software Engineering, Pearson. [10th ed.]."},{"key":"ref_29","first-page":"45","article-title":"Software Development Methodologies: A Comparative Analysis","volume":"83","author":"Anghel","year":"2022","journal-title":"UPB Sci. Bull"},{"key":"ref_30","first-page":"36407","article-title":"Deductive Verification of Chain-of-Thought Reasoning","volume":"36","author":"Ling","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, L.H., Hessel, J., Yu, Y., Ren, X., Chang, K.W., and Choi, Y. (2023, January 9\u201314). Symbolic Chain-of-Thought Distillation: Small Models Can Also \u201cThink\u201d Step-by-Step. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Toronto, ON, Canada.","DOI":"10.18653\/v1\/2023.acl-long.150"},{"key":"ref_32","unstructured":"Cormen, T.H., Leiserson, C., Rivest, R., and Stein, C. (2009). Introduction to Algorithms, MIT Press."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/0004-3702(85)90083-9","article-title":"Top-Down Synthesis of Divide-and-Conquer Algorithms","volume":"27","author":"Smith","year":"1985","journal-title":"Artif. Intell."},{"key":"ref_34","first-page":"153","article-title":"Separation of Concerns: Techniques, Issues and Implications","volume":"15","author":"Daga","year":"2006","journal-title":"J. Intell. Syst."},{"key":"ref_35","unstructured":"Walls, C. (2022). Spring in Action, Manning."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2164","DOI":"10.1016\/j.dss.2006.06.011","article-title":"Self-healing systems\u2014Survey and synthesis","volume":"42","author":"Ghosh","year":"2007","journal-title":"Decis. Support Syst."},{"key":"ref_37","unstructured":"(2025, March 01). Claude Sonnet Official Website. Available online: https:\/\/claude.ai\/."},{"key":"ref_38","unstructured":"(2025, March 01). Claude 3.5 Sonnet Announcement. Available online: https:\/\/www.anthropic.com\/news\/claude-3-5-sonnet."},{"key":"ref_39","unstructured":"Fielding, R.T. (2000). Architectural Styles and the Design of Network-Based Software Architectures. [Ph.D. Thesis, University of California]."},{"key":"ref_40","unstructured":"Martin, R.C. (2008). Clean Code: A Handbook of Agile Software Craftsmanship, Pearson."}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/14\/3\/94\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:48:07Z","timestamp":1760028487000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/14\/3\/94"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,6]]},"references-count":40,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["computers14030094"],"URL":"https:\/\/doi.org\/10.3390\/computers14030094","relation":{},"ISSN":["2073-431X"],"issn-type":[{"value":"2073-431X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,6]]}}}