Variability-Driven User-Story Generation using LLM and Triadic Concept Analysis
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arXiv
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| Format: | Preprint |
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2025
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| author | Bazin, Alexandre Gutierrez, Alain Huchard, Marianne Martin, Pierre Yulin Zhang |
| author_facet | Bazin, Alexandre Gutierrez, Alain Huchard, Marianne Martin, Pierre Yulin Zhang |
| contents | A widely used Agile practice for requirements is to produce a set of user stories (also called ``agile product backlog''), which roughly includes a list of pairs (role, feature), where the role handles the feature for a certain purpose. In the context of Software Product Lines, the requirements for a family of similar systems is thus a family of user-story sets, one per system, leading to a 3-dimensional dataset composed of sets of triples (system, role, feature). In this paper, we combine Triadic Concept Analysis (TCA) and Large Language Model (LLM) prompting to suggest the user-story set required to develop a new system relying on the variability logic of an existing system family. This process consists in 1) computing 3-dimensional variability expressed as a set of TCA implications, 2) providing the designer with intelligible design options, 3) capturing the designer's selection of options, 4) proposing a first user-story set corresponding to this selection, 5) consolidating its validity according to the implications identified in step 1, while completing it if necessary, and 6) leveraging LLM to have a more comprehensive website. This process is evaluated with a dataset comprising the user-story sets of 67 similar-purpose websites. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08666 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Variability-Driven User-Story Generation using LLM and Triadic Concept Analysis Bazin, Alexandre Gutierrez, Alain Huchard, Marianne Martin, Pierre Yulin Zhang Software Engineering Artificial Intelligence A widely used Agile practice for requirements is to produce a set of user stories (also called ``agile product backlog''), which roughly includes a list of pairs (role, feature), where the role handles the feature for a certain purpose. In the context of Software Product Lines, the requirements for a family of similar systems is thus a family of user-story sets, one per system, leading to a 3-dimensional dataset composed of sets of triples (system, role, feature). In this paper, we combine Triadic Concept Analysis (TCA) and Large Language Model (LLM) prompting to suggest the user-story set required to develop a new system relying on the variability logic of an existing system family. This process consists in 1) computing 3-dimensional variability expressed as a set of TCA implications, 2) providing the designer with intelligible design options, 3) capturing the designer's selection of options, 4) proposing a first user-story set corresponding to this selection, 5) consolidating its validity according to the implications identified in step 1, while completing it if necessary, and 6) leveraging LLM to have a more comprehensive website. This process is evaluated with a dataset comprising the user-story sets of 67 similar-purpose websites. |
| title | Variability-Driven User-Story Generation using LLM and Triadic Concept Analysis |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2504.08666 |