You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)

  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)

  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required

  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Using NLP tools to detect ambiguities in system requirements - A comparison study

Fulltext:


Publication Type:

Conference/Workshop Paper

Venue:

5th Workshop on Natural Language Processing for Requirements Engineering @ REFSQ


Abstract

Requirements engineering is a time-consuming process, and it can benefit significantly from automated tool support. Ambiguity detection in natural language requirements is a challenging problem in the requirements engineering community. Several Natural Language Processing tools and techniques have been developed to improve and solve the problem of ambiguity detection in natural language requirements. However, there is a lack of empirical evaluation of these tools. We aim to contribute the understanding of the empirical performance of such solutions by evaluating four tools using the dataset of 180 system requirements from the electric train propulsion system provided to us by our industrial partner Alstom. The tools that were selected for this study are Automated Requirements Measurement (ARM), Quality Analyzer for Requirement Specifications (QuARS), REquirements Template Analyzer (RETA), and Requirements Complexity Measurement (RCM). Our analysis showed that selected tools could achieve high recall. Two of them had the recall of 0.85 and 0.98. But they struggled to achieve high precision. The RCM, an in-house developed tool by our industrial partner Alstom, achieved the highest precision in our study of 0.68.

Bibtex

@inproceedings{Bajceta6390,
author = {Aleksandar Bajceta and Miguel Leon Ortiz and Wasif Afzal and Pernilla Lindberg and Markus Bohlin},
title = {Using NLP tools to detect ambiguities in system requirements - A comparison study},
month = {March},
year = {2022},
booktitle = {5th Workshop on Natural Language Processing for Requirements Engineering @ REFSQ},
url = {http://www.ipr.mdh.se/publications/6390-}
}