CASE Tool support for variability management in software product lines

Article


Bashroush, R., Garba, M., Rabiser, R., Groher, I. and Botterweck, G. 2017. CASE Tool support for variability management in software product lines. ACM Computing Surveys. 50 (Art. 14). https://doi.org/10.1145/3034827
AuthorsBashroush, R., Garba, M., Rabiser, R., Groher, I. and Botterweck, G.
Abstract

Software product lines (SPL) aim at reducing time-to-market and increasing software quality through extensive, planned reuse of artifacts. An essential activity in SPL is variability management, i.e., defining and managing commonality and variability among member products. Due to the large scale and complexity of today’s software-intensive systems, variability management has become increasingly complex to conduct. Accordingly, tool support for variability management has been gathering increasing momentum over the last few years and can be considered a key success factor for developing and maintaining SPLs. While several studies have already been conducted on variability management, none of these analyzed the available tool support in detail. In this work, we report on a survey in which we analyzed 37 existing variability management tools identified using a systematic literature review to understand the tools’ characteristics, maturity, and the challenges in the field. We conclude that while most studies on variability management tools provide a good motivation and description of the research context and challenges, they often lack empirical data to support their claims and findings. It was also found that quality attributes important for the practical use of tools such as usability, integration, scalability, and performance were out of scope for most studies.

JournalACM Computing Surveys
Journal citation50 (Art. 14)
ISSN0360-0300
1557-7341
Year2017
PublisherAssociation for Computing Machinery (ACM)
Accepted author manuscript
License
File Access Level
Anyone
Digital Object Identifier (DOI)https://doi.org/10.1145/3034827
Publication dates
Print01 Apr 2017
Publication process dates
Deposited02 Feb 2017
Accepted10 Jan 2017
FunderChristian Doppler Forschungsgesellschaft
Primetals Technologies Austria
Science Foundation Ireland (SFI)
Christian Doppler Forschungsgesellschaft
Primetals Technologies Austria
Science Foundation Ireland
Science Foundation Ireland
Copyright information© 2017 ACM.
Additional information

This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys, Vol. 50, ISS. 1, (01/04/2017) http://dx.doi.org/10.1145/3034827

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