Aug 30, 2024 · We report on a comparative study between AppStore- and LLM-based approaches for refining features into sub-features.

Oct 27, 2024 · We report on a comparative study between AppStore- and LLM-based approaches for refining features into sub-features. By manually analyzing 1,200 ...

While both approaches recommend highly relevant sub-features with clear descriptions, LLMs seem more powerful particularly concerning novel unseen app scopes.

We report on a comparative study between AppStore- and LLM-based approaches for refining features into sub-features. By manually analyzing 1,200 sub-features ...

Sep 11, 2024 · We report on a comparative study between AppStore- and LLM-based approaches for refining features into sub-features. By manually analyzing 1,200 ...

Oct 29, 2024 · We propose an alternative approach based on agent-based modeling (ABM) and inspired by the behavior of the Plasmodium mold, which builds ...

Sep 2, 2024 · Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach. https://arxiv.org/abs/2408.17404 · 8:19 AM · Sep 2, 2024.

Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach. About the project. The code of LLM-inspired approach is in llm.py . The code ...

We report on a comparative study between AppStore- and LLM-based approaches for refining features into sub-features. By manually analyzing 1,200 sub-features ...

This paper empirically analyse app store-inspired elicitation in a realistic scenario, in which it is used to extend the requirements of a product that were ...