Title :
Automated Concept Location Using Independent Component Analysis
Author :
Grant, Scott ; Cordy, James R. ; Skillicorn, David
Author_Institution :
Sch. of Comput., Queen´´s Univ. Kingston, Kingston, ON
Abstract :
Concept location techniques are designed to help isolate sections of source code that relate to specific concepts. Blind Signal Separation techniques like Singular Value Decomposition and Latent Semantic Indexing can be used as a way to identify related sections of source code. This paper explores a related technique called Independent Component Analysis that has the added benefit of identifying statistically independent signals in text, as opposed to ones that are just decorrelated. We describe a tool that we have developed to explore how ICA performs when analysing source code, and show how the technique can be used to perform unsupervised concept location.
Keywords :
blind source separation; independent component analysis; singular value decomposition; automated concept location; blind signal separation techniques; concept location techniques; independent component analysis; latent semantic indexing; singular value decomposition; source code sections; unsupervised concept location; Blind source separation; Data mining; Decorrelation; Independent component analysis; Indexing; Microphones; Performance analysis; Reverse engineering; Signal processing; Singular value decomposition; blind signal separation; concept location; independent component analysis;
Conference_Titel :
Reverse Engineering, 2008. WCRE '08. 15th Working Conference on
Conference_Location :
Antwerp
Print_ISBN :
978-0-7695-3429-9
DOI :
10.1109/WCRE.2008.49