TY - GEN
T1 - An empirical study of pre-release software faults in an industrial product line
AU - Devine, Thomas R.
AU - Goseva-Popstajanova, Katerina
AU - Krishnan, Sandeep
AU - Lutz, Robyn R.
AU - Li, J. Jenny
PY - 2012
Y1 - 2012
N2 - There is a lack of published studies providing empirical support for the assumption at the heart of product line development, namely, that through structured reuse later products will be less fault-prone. This paper presents results from an empirical study of pre-release fault and change proneness from four products in an industrial software product line. The objectives of the study are (1) to determine the association between various software metrics, as well as their correlation with the number of faults at the component level, (2) to characterize the fault and change proneness at various degrees of reuse, and (3) to determine how existing products in the software product line affect the quality of subsequently developed products and our ability to make predictions. The research results confirm, in a software product line setting, the findings of others that faults are more highly correlated to change metrics than to static code metrics. Further, the results show that variation components unique to individual products have the highest fault density and are the most prone to change. The longitudinal aspect of our research indicates that new products in this software product line benefit from the development and testing of previous products. For this case study, the number of faults in variation components of new products is predicted accurately using a linear model built on data from the previous products.
AB - There is a lack of published studies providing empirical support for the assumption at the heart of product line development, namely, that through structured reuse later products will be less fault-prone. This paper presents results from an empirical study of pre-release fault and change proneness from four products in an industrial software product line. The objectives of the study are (1) to determine the association between various software metrics, as well as their correlation with the number of faults at the component level, (2) to characterize the fault and change proneness at various degrees of reuse, and (3) to determine how existing products in the software product line affect the quality of subsequently developed products and our ability to make predictions. The research results confirm, in a software product line setting, the findings of others that faults are more highly correlated to change metrics than to static code metrics. Further, the results show that variation components unique to individual products have the highest fault density and are the most prone to change. The longitudinal aspect of our research indicates that new products in this software product line benefit from the development and testing of previous products. For this case study, the number of faults in variation components of new products is predicted accurately using a linear model built on data from the previous products.
KW - change metrics
KW - longitudinal study
KW - pre-release software faults
KW - reuse
KW - Software product lines
KW - static code metrics
UR - http://www.scopus.com/inward/record.url?scp=84862323227&partnerID=8YFLogxK
U2 - 10.1109/ICST.2012.98
DO - 10.1109/ICST.2012.98
M3 - Conference contribution
AN - SCOPUS:84862323227
SN - 9780769546704
T3 - Proceedings - IEEE 5th International Conference on Software Testing, Verification and Validation, ICST 2012
SP - 181
EP - 190
BT - Proceedings - IEEE 5th International Conference on Software Testing, Verification and Validation, ICST 2012
T2 - 5th IEEE International Conference on Software Testing, Verification and Validation, ICST 2012
Y2 - 17 April 2012 through 21 April 2012
ER -