Transactions on Software Engineering

The IEEE Transactions on Software Engineering (TSE) is an archival journal published bimonthly. We are interested in well-defined theoretical results and empirical studies that have potential impact on the construction, analysis, or management of software. Read the full scope of TSE.


Expand your horizons with Colloquium, a monthly survey of abstracts from all CS transactions! Replaces OnlinePlus in January 2017.


From the October 2017 Issue

Automated Extraction and Clustering of Requirements Glossary Terms

By Chetan Arora, Mehrdad Sabetzadeh, Lionel Briand, and Frank Zimmer

Featured article thumbnail image A glossary is an important part of any software requirements document. By making explicit the technical terms in a domain and providing definitions for them, a glossary helps mitigate imprecision and ambiguity. A key step in building a glossary is to decide upon the terms to include in the glossary and to find any related terms. Doing so manually is laborious, particularly for large requirements documents. In this article, we develop an automated approach for extracting candidate glossary terms and their related terms from natural language requirements documents. Our approach differs from existing work on term extraction mainly in that it clusters the extracted terms by relevance, instead of providing a flat list of terms. We provide an automated, mathematically-based procedure for selecting the number of clusters. This procedure makes the underlying clustering algorithm transparent to users, thus alleviating the need for any user-specified parameters. To evaluate our approach, we report on three industrial case studies, as part of which we also examine the perceptions of the involved subject matter experts about the usefulness of our approach. Our evaluation notably suggests that: (1) Over requirements documents, our approach is more accurate than major generic term extraction tools. Specifically, in our case studies, our approach leads to gains of 20 percent or more in terms of recall when compared to existing tools, while at the same time either improving precision or leaving it virtually unchanged. And, (2) the experts involved in our case studies find the clusters generated by our approach useful as an aid for glossary construction.

download PDF View the PDF of this article      csdl View this issue in the digital library      TSE Facebook Link  TSE on Facebook


Editorials and Announcements

Announcements

  • According to Clarivate Analytics' 2016 Journal Citation Report, TSE has an impact factor of 3.272.

Editorials


Reviewers List


Annual Index


Access All Recently Published TSE Articles

RSS Subscribe to the RSS feed of latest TSE content added to the digital library


Access TSE preprints in the Computer Society Digital Library

A preprint is an article that has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.