We first introduce the applicaiton domain, before describing our approach to requirements satisfiability using in-context learning, which proceeds in three ...
Apr 19, 2024 · The overall results show that GPT-4 can be used to verify requirements satisfaction with 96.7% accuracy and dissatisfaction with 93.2% accuracy.
In this paper, we apply ICL to the design and evaluation of satisfaction arguments, which describe how a requirement is satisfied by a system specification.
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Aug 24, 2024 · Context-aware applications monitor changes in their environment and switch their behaviour in order to continue satisfying requirements.
Jul 26, 2024 · ... Requirements Satisfiability with In-Context Learning” and won the RE24 Challenge Award for Research Track at the RE24 Conference. The ...
cmu-relab/req_sat: Replication Package for Requirements ... - GitHub
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"Requirements Satsifiability with In-Context Learning," IEEE International Requirements Engineering Conference, Reykavik, Iceland, 2024.
2024. Requirements Engineering. Requirements Satisfiability with In-Context Learning. Show activities from other conferences. Share. Requirements Engineering ...
Jul 12, 2024 · The paper, “Requirements Satisfiability With In-Context Learning,” builds on advances in large language models (LLMs) to show how authoritative ...
Co-authors ; Requirements Satisfiability with In-Context Learning. S Santos, T Breaux, T Norton, S Haghighi, S Ghanavati. The 32nd IEEE Requirements Engineering ...
Sep 30, 2024 · In-context learning is an emergent behaviour in pre-trained LLMs where the model seems to perform task inference (learn to do a task) and to ...