Can Text Mining Assistants Help to Improve Requirements Specifications?
|Title||Can Text Mining Assistants Help to Improve Requirements Specifications?|
|Publication Type||Conference Paper|
|Year of Publication||2012|
|Authors||Sateli B, Angius E, Rajivelu SSembakkam, Witte R|
|Conference Name||Mining Unstructured Data (MUD 2012)|
|Date Published||October 17|
|Conference Location||Kingston, Ontario, Canada|
|Keywords||natural language processing, Requirements Engineering, semantic Wiki|
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.