Authors:
Hans-Gerhard Gross
1
;
Marco Lormans
1
and
Jun Zhou
2
Affiliations:
1
Software Engineering Research Group, Delft University of Technology, Netherlands
;
2
The First Research Institute of the Ministry for Public Security, China
Keyword(s):
Latent Semantic Analysis, Component Identification, Component Selection, Procurement Automation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Software Development
;
Component-Based Software Engineering
;
Model-Driven Software Development
;
Software Engineering
Abstract:
One of the first steps of component procurement is the identification of required component features in large repositories of existing components. On the highest level of abstraction, component requirements as well as component descriptions are usually written in natural language. Therefore, we can reformulate component identification as a text analysis problem and apply latent semantic analysis for automatically identifying suitable existing components in large repositories, based on the descriptions of required component features. In this article, we motivate our choice of this technique for feature identification, describe how it can be applied to feature tracing problems, and discuss the results that we achieved with the application of this technique in a number of case studies.