ReXCL: A Tool for Requirement Document Extraction and Classification
This addresses the problem of manual requirement management for software developers, but it is incremental as it builds on existing methods like heuristics and encoder-based models.
The paper tackles automating requirement document extraction and classification in software engineering, resulting in a tool that improves efficiency and accuracy in managing requirements.
This paper presents the ReXCL tool, which automates the extraction and classification processes in requirement engineering, enhancing the software development lifecycle. 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.