A Novel Sentence Segmentation Approach for Test Cases Using NLP
A Novel Sentence Segmentation Approach for Test Cases Using NLP
17 PagesThis paper introduces an AI-driven NLP model that segments complex test steps into simpler, actionable phrases. Using machine learning and deep learning, it identifies conjunctions/prepositions to preserve meaning and order. Integrated with the TAROT engine, it enhances keyword extraction for automation frameworks like FALCON. The approach improves test automation accuracy, reduces manual effort, and strengthens AI-based testing intelligence.
