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Towards an automatic contradiction detection in requirements engineering
Published online by Cambridge University Press: 16 May 2024
Abstract
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This paper presents a novel method for automatic contradiction detection in requirements engineering using a hybrid approach combining formal logic with Large Language Models (LLMs), specifically GPT-3. Our three-phase process detects contradictions by identifying conditionals and pseudo-grammatical elements, and employing LLMs for nuanced contradiction detection. Tested extensively, including on a real-world electric bus project, our method achieved 99% accuracy and 60% recall. This approach significantly reduces manual effort, enhances quality, and is scalable for future advancements.
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- Artificial Intelligence and Data-Driven Design
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- Creative Commons
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.- Copyright
- The Author(s), 2024.
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