Read, Extract, Classify: A Tool for Smarter Requirements Engineering
For requirements engineers, this tool automates a labor-intensive task, but the novelty is incremental as it combines existing NLP techniques.
The paper introduces ReXCL, a tool that automates extraction and classification of requirements from semi-structured documents, improving efficiency and accuracy in requirements engineering.
This paper presents the ReXCL tool, which automates the extraction and classification processes in requirements engineering, enhancing the software development life-cycle. The tool features two main modules: Extraction, which processes raw requirement documents into a predefined schema using heuristics and predictive modeling, and Classification, which assigns class labels to requirements using adaptive fine-tuning of encoder-based models. The final output can be exported to external requirement engineering tools. Performance evaluations indicate that ReXCL significantly improves efficiency and accuracy in managing requirements, marking a novel approach to automating the schematization of semi-structured requirement documents.