The Open UniversitySkip to content
 

Automatic detection of nocuous coordination ambiguities in natural language requirements

Yang, Hui; Willis, Alistair; De Roeck, Anne and Nuseibeh, Bashar (2010). Automatic detection of nocuous coordination ambiguities in natural language requirements. In: The IEEE/ACM international conference on Automated software engineering (ASE'10), 20–24 Sep 2010, Antwerp, Belgium, ACM, pp. 53–62.

Full text available as:
Full text not publicly available
Due to copyright restrictions, this file is not available for public download
Click here to request a copy from the OU Author.
DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1145/1858996.1859007
Google Scholar: Look up in Google Scholar

Abstract

Natural language is prevalent in requirements documents. However, ambiguity is an intrinsic phenomenon of natural language, and is therefore present in all such documents. Ambiguity occurs when a sentence can be interpreted differently by different readers. In this paper, we describe an automated approach for characterizing and detecting so-called nocuous ambiguities, which carry a high risk of misunderstanding among different readers. Given a natural language requirements document, sentences that contain specific types of ambiguity are first extracted automatically from the text. A machine learning algorithm is then used to determine whether an ambiguous sentence is nocuous or innocuous, based on a set of heuristics that draw on human judgments, which we collected as training data. We implemented a prototype tool for Nocuous Ambiguity Identification (NAI), in order to illustrate and evaluate our approach. The tool focuses on coordination ambiguity. We report on the results of a set of experiments to assess the performance and usefulness of the approach.

Item Type: Conference Item
Copyright Holders: 2010 ACM
ISBN: 1-4503-0116-9, 978-1-4503-0116-9
Keywords: natural language requirements; nocuous ambiguity; coordination ambiguity; machine learning; human judgments
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 23771
Depositing User: Hui Yang
Date Deposited: 27 Oct 2010 11:24
Last Modified: 12 Dec 2012 20:04
URI: http://oro.open.ac.uk/id/eprint/23771
Share this page:

Altmetrics

Scopus Citations

Actions (login may be required)

View Item
Report issue / request change

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk