Automated User Story Generation with Test Case Specification Using Large Language Model
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Abstract (arXiv)
Modern Software Engineering era is moving fast with the assistance of artificial intelligence (AI), especially Large Language Models (LLM). Researchers have already started automating many parts of the software development workflow. Requirements Engineering (RE) is a crucial phase that begins the software development cycle through multiple discussions on a proposed scope of work documented in different forms. RE phase ends with a list of user-stories for each unit task identified through discussions and usually these are created and tracked on a project management tool such as Jira, AzurDev etc. In this research we developed a tool "GeneUS" using GPT-4.0 to automatically create user stories from requirements document which is the outcome of the RE phase. The output is provided in JSON format leaving the possibilities open for downstream integration to the popular project management tools. Analyzing requirements documents takes significant effort and multiple meetings with stakeholders. We believe, automating this process will certainly reduce additional load off the software engineers, and increase the productivity since they will be able to utilize their time on other prioritized tasks.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 17 of its 39 references that are in the map. First posted on arXiv 2 Apr 2024.
Builds on
17 of 39 references.
References · 17
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5 more
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Built on by
Citing papers per year: 2024: 3; 2025: 2; 2026: 2.
7 papers.
- 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Futurecited by 85
- 2024Using LLMs in Software Requirements Specifications: An Empirical Evaluationcited by 20
- 2025Reverse Engineering User Stories from Code using Large Language Modelscited by 2
- 2024System Test Case Design from Requirements Specifications: Insights and Challenges of Using ChatGPTcited by 1
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standardscited by 1
- 2026From Reviews to Requirements: Can LLMs Generate Human-Like User Stories?cited by 0
- 2026How Well Can AI Generate Backlogs from App Mockups?cited by 0
- 2026How Well Can AI Generate Backlogs from App Mockups?24 Jul 2026
- 2026From Reviews to Requirements: Can LLMs Generate Human-Like User Stories?30 Mar 2026
- 2025Reverse Engineering User Stories from Code using Large Language Models23 Sep 2025
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards19 May 2025
- 2024System Test Case Design from Requirements Specifications: Insights and Challenges of Using ChatGPT4 Dec 2024
- 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future5 Aug 2024
- 2024Using LLMs in Software Requirements Specifications: An Empirical Evaluation27 Apr 2024