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Automated User Story Generation with Test Case Specification Using Large Language Model

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arxiv 2404.01558 v1 pith:BA4KFERA submitted 2024-04-02 cs.SE cs.AI

Automated User Story Generation with Test Case Specification Using Large Language Model

classification cs.SE cs.AI
keywords softwarephaserequirementsautomatingdevelopmentdiscussionsengineeringlanguage
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. LLMCFG-TGen: Using LLM-Generated Control Flow Graphs to Automatically Create Test Cases from Use Cases

    cs.SE 2025-12 conditional novelty 6.0

    An LLM-generated control-flow graph intermediate representation improves completeness and reduces redundancy in test cases generated from natural-language use cases.

  2. A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards

    cs.SE 2025-05 unverdicted novelty 3.0

    Survey mapping LLM applications in software quality assurance to established standards including ISO/IEC 12207, ISO 25010, CMMI, and TMM, with case studies, challenges, and future directions.