| Title | Can Text Mining Assistants Help to Improve Requirements Specifications? |
| Publication Type | Conference Paper |
| Year of Publication | 2012 |
| Refereed Designation | Refereed |
| Authors | Sateli, B. [7], E. Angius [8], S. S. Rajivelu [9], and R. Witte [10] |
| Conference Name | Mining Unstructured Data (MUD 2012) |
| Date Published | October 17 |
| Conference Location | Kingston, Ontario, Canada |
| Type of Work | Paper |
| Keywords | natural language processing [11], Requirements Engineering [12], semantic Wiki [13] |
| Abstract | Software requirements specifications are commonly written in natural language, making them prone to a number of defects, such as ambiguity, inconsistency, or lack of readability. Natural Language Processing (NLP) techniques have been proposed as a means to (semi-)automatically improve requirements specifications, but so far have not been widely adopted. We integrated a number of text mining assistants into a wiki-based requirements engineering platform to investigate two key questions: Can software engineers without prior training in NLP effectively leverage these techniques? And are text mining assistants actually helpful in improving the quality of a specification? Results obtained during two software engineering courses demonstrate that both are indeed the case. |
| URL | http://sailhome.cs.queensu.ca/mud/res/sateli-mud2012.pdf [14] |
| Copyright | © 2012 Bahar Sateli, Elian Angius, Srinivasan Sembakkam Rajivelu and René Witte |
| Attachment | Size |
|---|---|
| mud2012-ReqWiki.pdf [15] | 375.44 KB |
