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Exploring LLMs’ Ability to Detect Variability in Requirements

  • Alessandro Fantechi,
  • Stefania Gnesi,
  • Laura Semini

摘要

In this paper, we address the question of whether general-purpose LLM-based tools may be useful for detecting requirements variability in Natural Language (NL) requirements documents. For this purpose, we conduct a preliminary exploratory study considering OpenAI chatGPT-3.5 and Microsoft Bing. Using two exemplar NL requirements documents, we compare the variability detection capability of the chatbots with that of experts and that of a rule-based NLP tool.