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.
| Original language | English |
|---|---|
| Article number | 14 |
| Number of pages | 45 |
| Journal | ACM Computing Surveys |
| Volume | 50 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Mar 2017 |
Fields of science
- 202005 Computer architecture
- 202017 Embedded systems
- 102 Computer Sciences
- 102002 Augmented reality
- 102006 Computer supported cooperative work (CSCW)
- 102011 Formal languages
- 102015 Information systems
- 102020 Medical informatics
- 102022 Software development
- 102027 Web engineering
- 201305 Traffic engineering
- 202022 Information technology
- 207409 Navigation systems
- 502032 Quality management
- 502050 Business informatics
JKU Focus areas
- Computation in Informatics and Mathematics
- Management and Innovation
Projects
- 1 Finished
-
Christian Doppler Labor für Monitoring and Evolution of Very-Large-Scale Software Systems
Grünbacher, P. (PI)
01.02.2013 → 31.08.2020
Project: Funded research › CDG - Christian Doppler Forschungsgesellschaft
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver