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Title:
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ENHANCING END-TO-END USER STORY CREATION WITH OPEN-SOURCE LARGE LANGUAGE MODELS: A GUIDED CHAIN-OF-THOUGHT METHOD |
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Author(s):
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Andrius Dalisanskis and Enda Fallon |
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ISBN:
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978-989-8704-62 |
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Editors:
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Paula Miranda and Pedro Isaías |
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Year:
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2024 |
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Edition:
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Single |
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Keywords:
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Prompt Engineering, LLM, User Story Automation |
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Type:
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Full |
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First Page:
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143 |
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Last Page:
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150 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper presents the results from a study aimed at enhancing agile project management through the automated creation and integration of user stories using open-source large language models (LLMs) with a proposed Guided Chain-of-Thought prompting framework. The study evaluates the effectiveness of this approach in reducing manual workload and improving user satisfaction. Findings demonstrate significant efficiency gains and positive user feedback, indicating the potential for broad adoption in real-world agile environments. |
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