RITA: A Tool for Automated Requirements Classification and Specification from Online User Feedback
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866914259366051840 |
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| author | Mallya, Manjeshwar Aniruddh Ferrari, Alessio Zadenoori, Mohammad Amin Dąbrowski, Jacek |
| author_facet | Mallya, Manjeshwar Aniruddh Ferrari, Alessio Zadenoori, Mohammad Amin Dąbrowski, Jacek |
| contents | Context and motivation. Online user feedback is a valuable resource for requirements engineering, but its volume and noise make analysis difficult. Existing tools support individual feedback analysis tasks, but their capabilities are rarely integrated into end-to-end support. Problem. The lack of end-to-end integration limits the practical adoption of existing RE tools and makes it difficult to assess their real-world usefulness. Solution. To address this challenge, we present RITA, a tool that integrates lightweight open-source large language models into a unified workflow for feedback-driven RE. RITA supports automated request classification, non-functional requirement identification, and natural-language requirements specification generation from online feedback via a user-friendly interface, and integrates with Jira for seamless transfer of requirements specifications to development tools. Results and conclusions. RITA exploits previously evaluated LLM-based RE techniques to efficiently transform raw user feedback into requirements artefacts, helping bridge the gap between research and practice. A demonstration is available at: https://youtu.be/8meCLpwQWV8. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_11362 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | RITA: A Tool for Automated Requirements Classification and Specification from Online User Feedback Mallya, Manjeshwar Aniruddh Ferrari, Alessio Zadenoori, Mohammad Amin Dąbrowski, Jacek Software Engineering Context and motivation. Online user feedback is a valuable resource for requirements engineering, but its volume and noise make analysis difficult. Existing tools support individual feedback analysis tasks, but their capabilities are rarely integrated into end-to-end support. Problem. The lack of end-to-end integration limits the practical adoption of existing RE tools and makes it difficult to assess their real-world usefulness. Solution. To address this challenge, we present RITA, a tool that integrates lightweight open-source large language models into a unified workflow for feedback-driven RE. RITA supports automated request classification, non-functional requirement identification, and natural-language requirements specification generation from online feedback via a user-friendly interface, and integrates with Jira for seamless transfer of requirements specifications to development tools. Results and conclusions. RITA exploits previously evaluated LLM-based RE techniques to efficiently transform raw user feedback into requirements artefacts, helping bridge the gap between research and practice. A demonstration is available at: https://youtu.be/8meCLpwQWV8. |
| title | RITA: A Tool for Automated Requirements Classification and Specification from Online User Feedback |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2601.11362 |