by Gabriela Karoline Michelon, David Obermann, Lukas Linsbauer, Wesley K. G. Assunção, Paul Grünbacher, Alexander Egyed
Abstract:
Software companies encounter variability in space as variants of software systems need to be produced for different customers. At the same time, companies need to handle evolution in time because the customized variants need to be revised and kept up-to-date. This leads to a predicament in practice with many system variants significantly diverging from each other. Maintaining these variants consistently is difficult, as they diverge across space, i.e., different feature combinations, and over time, i.e., revisions of features. This work presents an automated feature revision location technique that traces feature revisions to their implementation. To assess the correctness of our technique, we used variants and revisions from three open source highly configurable software systems. In particular, we compared the original artifacts of the variants with the composed artifacts that were located by our technique. The results show that our technique can properly trace feature revisions to their implementation, reaching traces with 100\% precision and 98\% recall on average for the three analyzed subject systems, taking on average around 50 seconds for locating feature revisions per variant used as input.
Reference:
Locating Feature Revisions in Software Systems Evolving in Space and Time (Gabriela Karoline Michelon, David Obermann, Lukas Linsbauer, Wesley K. G. Assunção, Paul Grünbacher, Alexander Egyed), In Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A, Association for Computing Machinery, 2020.
Bibtex Entry:
@Conference{DBLP:conf/splc/MichelonResearchTrack20,
author = {Gabriela Karoline Michelon and David Obermann and Lukas Linsbauer and Wesley K. G. Assunção and Paul Grünbacher and Alexander Egyed},
booktitle = {Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A},
title = {Locating Feature Revisions in Software Systems Evolving in Space and Time},
year = {2020},
address = {New York, NY, USA},
pages = {14:1--14:11},
publisher = {Association for Computing Machinery},
series = {SPLC '20},
abstract = {Software companies encounter variability in space as variants of software systems need to be produced for different customers. At the same time, companies need to handle evolution in time because the customized variants need to be revised and kept up-to-date. This leads to a predicament in practice with many system variants significantly diverging from each other. Maintaining these variants consistently is difficult, as they diverge across space, i.e., different feature combinations, and over time, i.e., revisions of features. This work presents an automated feature revision location technique that traces feature revisions to their implementation. To assess the correctness of our technique, we used variants and revisions from three open source highly configurable software systems. In particular, we compared the original artifacts of the variants with the composed artifacts that were located by our technique. The results show that our technique can properly trace feature revisions to their implementation, reaching traces with 100\% precision and 98\% recall on average for the three analyzed subject systems, taking on average around 50 seconds for locating feature revisions per variant used as input.},
articleno = {14},
doi = {10.1145/3382025.3414954},
file = {:Conferences/ACM 2020 - Locating feature revisions in software systems evolving in space and time/Locating feature revisions in software systems evolving in space and time-preprint.pdf:PDF},
isbn = {9781450375696},
keywords = {LIT Secure and Correct Systems Lab, FWF P31989, Pro2Future},
location = {Montreal, Quebec, Canada},
numpages = {11},
url = {https://doi.org/10.1145/3382025.3414954},
}