Requirements are All You Need: From Requirements to Code with LLMs
Not on the map. Why?
Abstract (arXiv)
The pervasive use of textual formats in the documentation of software requirements presents a great opportunity for applying large language models (LLMs) to software engineering tasks. High-quality software requirements not only enhance the manual software development process but also position organizations to fully harness the potential of the emerging LLMs technology. This paper introduces a tailored LLM for automating the generation of code snippets from well-structured requirements documents. This LLM is augmented with knowledge, heuristics, and instructions that are pertinent to the software development process, requirements analysis, object-oriented design, and test-driven development, effectively emulating the expertise of a seasoned software engineer. We introduce a "Progressive Prompting" method that allows software engineers to engage with this LLM in a stepwise manner. Through this approach, the LLM incrementally tackles software development tasks by interpreting the provided requirements to extract functional requirements, using these to create object-oriented models, and subsequently generating unit tests and code based on the object-oriented designs. We demonstrate the LLM's proficiency in comprehending intricate user requirements and producing robust design and code solutions through a case study focused on the development of a web project. This study underscores the potential of integrating LLMs into the software development workflow to significantly enhance both efficiency and quality. The tailored LLM is available at https://chat.openai.com/g/g-bahoiKzkB-software-engineer-gpt.
Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jun 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 5; 2025: 11; 2026: 5.
21 papers.
Sort:
By area:
- 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Futurecited by 85
- 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AIcited by 39
- 2025Exploring Autonomous Agents: A Closer Look at Why They Fail When Completing Taskscited by 20
- 2025Generative AI for Software Architecture. Applications, Challenges, and Future Directionscited by 15
- 2024Generative AI for Requirements Engineering: A Systematic Literature Reviewcited by 10
- 2024Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysiscited by 6
- 2024Mitigating Gender Bias in Code Large Language Models via Model Editingcited by 3
- 2025Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Visioncited by 3
- 2025Assessing LLMs for Front-end Software Architecture Knowledgecited by 2
- 2025Can LLMs Generate User Stories and Assess Their Quality?cited by 2
- 2026The State of Generative AI in Software Development: Insights from Literature and a Developer Surveycited by 2
- 2025Goal2Story: A Multi-Agent Fleet based on Privately Enabled sLLMs for Impacting Mapping on Requirements Elicitationcited by 1
9 more
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standardscited by 1
- 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Reportcited by 1
- 2024Improving Performance of Commercially Available AI Products in a Multi-Agent Configurationcited by 0
- 2025LLM assisted web application functional requirements generation: A case study of four popular LLMs over a Mess Management Systemcited by 0
- 2025Application Modernization with LLMs: Addressing Core Challenges in Reliability, Security, and Qualitycited by 0
- 2025The Software Engineering Simulations Lab: Agentic AI for RE Quality Simulationscited by 0
- 2026HanoiWorld : A Joint Embedding Predictive Architecture BasedWorld Model for Autonomous Vehicle Controllercited by 0
- 2026Exploring LLMs for User Story Extraction from Mockupscited by 0
- 2026Integrating AI into Requirements Quality Learning in Software Engineering Education: A TPACK-Guided Empirical Studycited by 0
- 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report12 Aug 2026
- 2026Integrating AI into Requirements Quality Learning in Software Engineering Education: A TPACK-Guided Empirical Study30 Jul 2026
- 2026The State of Generative AI in Software Development: Insights from Literature and a Developer Survey17 Mar 2026
- 2026Exploring LLMs for User Story Extraction from Mockups19 Feb 2026
- 2026HanoiWorld : A Joint Embedding Predictive Architecture BasedWorld Model for Autonomous Vehicle Controller4 Jan 2026
- 2025The Software Engineering Simulations Lab: Agentic AI for RE Quality Simulations21 Nov 2025
- 2025Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision26 Aug 2025
- 2025Exploring Autonomous Agents: A Closer Look at Why They Fail When Completing Tasks18 Aug 2025
- 2025Can LLMs Generate User Stories and Assess Their Quality?20 Jul 2025
- 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI26 May 2025
- 2025LLM assisted web application functional requirements generation: A case study of four popular LLMs over a Mess Management System23 May 2025
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards19 May 2025
9 more
- 2025Generative AI for Software Architecture. Applications, Challenges, and Future Directions17 Mar 2025
- 2025Goal2Story: A Multi-Agent Fleet based on Privately Enabled sLLMs for Impacting Mapping on Requirements Elicitation17 Mar 2025
- 2025Assessing LLMs for Front-end Software Architecture Knowledge26 Feb 2025
- 2025Application Modernization with LLMs: Addressing Core Challenges in Reliability, Security, and Quality13 Feb 2025
- 2024Improving Performance of Commercially Available AI Products in a Multi-Agent Configuration29 Oct 2024
- 2024Mitigating Gender Bias in Code Large Language Models via Model Editing10 Oct 2024
- 2024Generative AI for Requirements Engineering: A Systematic Literature Review10 Sep 2024
- 2024Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysis23 Aug 2024
- 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future5 Aug 2024
- 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Futurecited by 85
- 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AIcited by 39
- 2025Exploring Autonomous Agents: A Closer Look at Why They Fail When Completing Taskscited by 20
- 2024Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysiscited by 6
- 2025Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Visioncited by 3
- 2025Goal2Story: A Multi-Agent Fleet based on Privately Enabled sLLMs for Impacting Mapping on Requirements Elicitationcited by 1
- 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Reportcited by 1
- 2024Improving Performance of Commercially Available AI Products in a Multi-Agent Configurationcited by 0
- 2025The Software Engineering Simulations Lab: Agentic AI for RE Quality Simulationscited by 0
- 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report12 Aug 2026
- 2025The Software Engineering Simulations Lab: Agentic AI for RE Quality Simulations21 Nov 2025
- 2025Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision26 Aug 2025
- 2025Exploring Autonomous Agents: A Closer Look at Why They Fail When Completing Tasks18 Aug 2025
- 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI26 May 2025
- 2025Goal2Story: A Multi-Agent Fleet based on Privately Enabled sLLMs for Impacting Mapping on Requirements Elicitation17 Mar 2025
- 2024Improving Performance of Commercially Available AI Products in a Multi-Agent Configuration29 Oct 2024
- 2024Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysis23 Aug 2024
- 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future5 Aug 2024
- 2025Generative AI for Software Architecture. Applications, Challenges, and Future Directionscited by 15
- 2024Generative AI for Requirements Engineering: A Systematic Literature Reviewcited by 10
- 2024Mitigating Gender Bias in Code Large Language Models via Model Editingcited by 3
- 2025Assessing LLMs for Front-end Software Architecture Knowledgecited by 2
- 2025Can LLMs Generate User Stories and Assess Their Quality?cited by 2
- 2026The State of Generative AI in Software Development: Insights from Literature and a Developer Surveycited by 2
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standardscited by 1
- 2025LLM assisted web application functional requirements generation: A case study of four popular LLMs over a Mess Management Systemcited by 0
- 2025Application Modernization with LLMs: Addressing Core Challenges in Reliability, Security, and Qualitycited by 0
- 2026Exploring LLMs for User Story Extraction from Mockupscited by 0
- 2026Integrating AI into Requirements Quality Learning in Software Engineering Education: A TPACK-Guided Empirical Studycited by 0
- 2026Integrating AI into Requirements Quality Learning in Software Engineering Education: A TPACK-Guided Empirical Study30 Jul 2026
- 2026The State of Generative AI in Software Development: Insights from Literature and a Developer Survey17 Mar 2026
- 2026Exploring LLMs for User Story Extraction from Mockups19 Feb 2026
- 2025Can LLMs Generate User Stories and Assess Their Quality?20 Jul 2025
- 2025LLM assisted web application functional requirements generation: A case study of four popular LLMs over a Mess Management System23 May 2025
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards19 May 2025
- 2025Generative AI for Software Architecture. Applications, Challenges, and Future Directions17 Mar 2025
- 2025Assessing LLMs for Front-end Software Architecture Knowledge26 Feb 2025
- 2025Application Modernization with LLMs: Addressing Core Challenges in Reliability, Security, and Quality13 Feb 2025
- 2024Mitigating Gender Bias in Code Large Language Models via Model Editing10 Oct 2024
- 2024Generative AI for Requirements Engineering: A Systematic Literature Review10 Sep 2024