The content describes the development of a tool called "GeneUS" that automatically generates user stories and test cases from software requirements documents using a large language model (LLM). The key points are:
The Agile software development process relies heavily on user stories, which are created manually from requirements documents, a time-consuming task. The authors aim to automate this process using LLMs.
The authors propose a novel prompting technique called "Refine and Thought" (RaT) to improve the performance of LLMs in handling complex and redundant input, which is a common challenge in processing software requirements documents.
The GeneUS tool takes a requirements document as input and generates detailed user stories, including information about the user, the functionality, the purpose, the definition of done, functional and non-functional constraints, and test specifications.
The authors conducted a survey with 50 software engineering professionals to evaluate the quality of the automatically generated user stories and test cases using the RUST (Readability, Understandability, Specifiability, Technical-aspects) framework.
The survey results show that the overall quality of the generated user stories is rated as "Good" (4 out of 5), with some room for improvement in the Specifiability and Technical-aspects categories.
The authors plan to further enhance the tool's performance by incorporating domain-specific knowledge and leveraging knowledge embedding techniques to address issues related to LLM hallucinations.
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arxiv.org
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by Tajmilur Rah... at arxiv.org 04-03-2024
https://arxiv.org/pdf/2404.01558.pdfDeeper Inquiries