Semi-Supervised Classification of Non-Functional Requirements: An Empirical Analysis

Agustin Casamayor, Daniela Godoy, Marcelo Campo
2010 Inteligencia Artificial  
The early detection and classification of non-functional requirements (NFRs) is not only a hard and time consuming process, but also crucial in the evaluation of architectural alternatives starting from initial design decisions. In this paper, we propose a recommender system based on a semi-supervised learning approach for assisting analysts in the detection and classification of NFRs from textual requirements descriptions. Classification relies on a reduced number of categorized requirements
more » ... d takes advantage of the knowledge provided by uncategorized ones as well as certain properties of text. Experimental results show that the proposed recommendation approach based on semi-supervised learning outperforms previous proposals for classifying different types of requirements.
doi:10.4114/ia.v13i44.1044 fatcat:ukwidini7zfi5iq4jqmz7eylha