Authors | D. Falessi, G. Cantone and G. Canfora |
Editors | G. Succi, M. Morisio and N. Nagappan |
Title | A Comprehensive Characterization of NLP Techniques for Identifying Equivalent Requirements |
Afilliation | Software Engineering, Software Engineering |
Status | Published |
Publication Type | Proceedings, refereed |
Year of Publication | 2010 |
Conference Name | International Symposium on Empirical Software Engineering and Measurement (ESEM 2010) |
Publisher | ACM |
ISBN Number | 978-1-4503-0039-1 |
Abstract | [Context] Though very important in software engineering, linking artifacts of the same type (clone detection) or of different types (traceability recovery) is extremely tedious, error-prone and requires significant effort. Past research focused on supporting analysts with mechanisms based on Natural Language Processing (NLP) to identify candidate links. Because a plethora of NLP techniques exists, and their performances vary among contexts, it is important to characterize them according to the provided level of support. [Objective] The aim of this paper is to characterize a comprehensive set of NLP techniques according to the provided level of support to the human analyst in detecting equivalent requirements. [Method] The characterization consists on a case study, featuring real requirements, in the context of an Italian company in the defense and aerospace domain. [Results] The major result from the case study is that simple NLP are more precise than complex ones. |
Citation Key | Simula.approve.24 |