Open AccessTowards Software Component Procurement Automation with Latent Semantic Analysis
Author(s) -
Hans-Gerhard Groß,
M. Lormans,
Jùn Zhou
Publication year - 2007
Publication title -
electronic notes in theoretical computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.242
H-Index - 60
ISSN - 1571-0661
DOI - 10.1016/j.entcs.2007.05.047
Subject(s) - component (thermodynamics) , computer science , procurement , feature (linguistics) , identification (biology) , tracing , latent semantic analysis , automation , software engineering , component based software engineering , abstraction , feature model , software , programming language , data mining , artificial intelligence , software development , engineering , mechanical engineering , linguistics , philosophy , physics , botany , epistemology , marketing , biology , business , thermodynamics
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 procurement 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
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