Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation
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 workf...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/14/3/94 |
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| author | Vladimir Sonkin Cătălin Tudose |
| author_facet | Vladimir Sonkin Cătălin Tudose |
| author_sort | Vladimir Sonkin |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e6a4e73b2b234a0383e3da82a352426e |
| institution | DOAJ |
| issn | 2073-431X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj-art-e6a4e73b2b234a0383e3da82a352426e2025-08-20T02:42:46ZengMDPI AGComputers2073-431X2025-03-011439410.3390/computers14030094Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code GenerationVladimir Sonkin0Cătălin Tudose1Luxoft Serbia, 11079 Beograd, SerbiaLuxoft Romania, 020335 Bucharest, RomaniaRecent 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.https://www.mdpi.com/2073-431X/14/3/94artificial intelligenceLLMAI code reviewprompt engineeringroutine taskssoftware development automation |
| spellingShingle | Vladimir Sonkin Cătălin Tudose Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation Computers artificial intelligence LLM AI code review prompt engineering routine tasks software development automation |
| title | Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation |
| title_full | Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation |
| title_fullStr | Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation |
| title_full_unstemmed | Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation |
| title_short | Beyond Snippet Assistance: A Workflow-Centric Framework for End-to-End AI-Driven Code Generation |
| title_sort | beyond snippet assistance a workflow centric framework for end to end ai driven code generation |
| topic | artificial intelligence LLM AI code review prompt engineering routine tasks software development automation |
| url | https://www.mdpi.com/2073-431X/14/3/94 |
| work_keys_str_mv | AT vladimirsonkin beyondsnippetassistanceaworkflowcentricframeworkforendtoendaidrivencodegeneration AT catalintudose beyondsnippetassistanceaworkflowcentricframeworkforendtoendaidrivencodegeneration |