Automated Requirement Formalization Using Product Design Specifications
Robin Gröpler, Libin Kutty, Viju Sudhi, Daran Smalley
In NLP4RE’22: 5th Workshop on Natural Language Processing for Requirements Engineering (REFSQ’22 Workshop)
Abstract:
Assuring the quality of complex and highly configurable software systems is a demanding and timeconsuming process. Especially for safety-critical systems, extensive testing based on requirements is necessary. Methods for model-based test automation in agile software development offer the possibility to overcome these difficulties. However, it is still a major effort to create formal models from functional requirements in natural language on a large scale. In this paper, we present and evaluate automated support for the requirements formalization process to reduce cost and effort. We present a new approach based on Natural Language Processing (NLP) and textual similarity using requirements and product design specifications to generate human-and machine-readable models. The method is evaluated on an industrial use case from the railway domain. The recommended requirement models for the considered propulsion system show an average accuracy of more than 90% and an exact match of the entire models of about 55%. These results show that our approach can support the requirements formalization process, which can be further used for test case generation and execution, as well as for requirements and design verification.
Full Text:
Bibtex:
@inproceedings{gropler2022automated,
title={Automated Requirement Formalization Using Product Design Specifications.},
author={Gr{\"o}pler, Robin and Kutty, Libin and Sudhi, Viju and Smalley, Daran},
booktitle={REFSQ Workshops},
year={2022}
}