TY - GEN
T1 - Feature location in a collection of product variants
AU - Xue, Yinxing
AU - Xing, Zhenchang
AU - Jarzabek, Stan
PY - 2012
Y1 - 2012
N2 - Companies often develop and maintain a collection of product variants that share some common features but also support different, customer-specific features. To reengineering such legacy product variants for systematic reuse, one must identify features and their implementing code units (e.g. functions, files) in different product variants. Information retrieval (IR) techniques may be applied for that purpose. In this paper, we discuss problems that hinder direct application of IR techniques to a collection of product variants. To counter these problems, we present an approach to support effective feature location in product variants. The novelty of our approach is that we exploit commonalities and differences of product variants by software differencing and FCA techniques so that IR technique can achieve satisfactory results for feature location in product variants. We have implemented our approach and conducted evaluation with a collection of nine Linux kernel product variants. Our evaluation shows that our approach always significantly outperforms a direct application of IR technique in the subject product variants.
AB - Companies often develop and maintain a collection of product variants that share some common features but also support different, customer-specific features. To reengineering such legacy product variants for systematic reuse, one must identify features and their implementing code units (e.g. functions, files) in different product variants. Information retrieval (IR) techniques may be applied for that purpose. In this paper, we discuss problems that hinder direct application of IR techniques to a collection of product variants. To counter these problems, we present an approach to support effective feature location in product variants. The novelty of our approach is that we exploit commonalities and differences of product variants by software differencing and FCA techniques so that IR technique can achieve satisfactory results for feature location in product variants. We have implemented our approach and conducted evaluation with a collection of nine Linux kernel product variants. Our evaluation shows that our approach always significantly outperforms a direct application of IR technique in the subject product variants.
KW - feature location
KW - formal concept analysis
KW - latent semantic analysis
KW - software differencing
KW - software product variants
UR - http://www.scopus.com/inward/record.url?scp=84872312622&partnerID=8YFLogxK
U2 - 10.1109/WCRE.2012.24
DO - 10.1109/WCRE.2012.24
M3 - Conference contribution
SN - 9780769548913
T3 - Proceedings - Working Conference on Reverse Engineering, WCRE
SP - 145
EP - 154
BT - Proceedings - 19th Working Conference on Reverse Engineering, WCRE 2012
T2 - 19th Working Conference on Reverse Engineering, WCRE 2012
Y2 - 15 October 2012 through 18 October 2012
ER -