Name
Abstract | ||
|---|---|---|
Testing software systems plays a pivotal role for quality, reliability, and safety of such systems. Several approaches exist that provide efficient algorithms to test one software system. However, in the context of variable software systems, called software product lines (SPLs), testing has to deal with potentially thousands of variants. Unfortunately, current approaches do not scale to this problem and thus testing SPLs efficiently is a challenging task. In this paper, we propose an approach to reduce the test set by explicitly modeling information about shared resources and communication in feature models. As a result, we can figure out features that interact with each other and thus are more likely to cause problems. We show with a small case study that our approach reduces both, the features under test as well as the time for computing all feature combinations to be tested. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2451617.2451619 | Proceedings of the 4th international workshop on Variability & composition |
Keywords | DocType | Citations |
variant reduction,software system,testing software system,challenging task,feature model,pivotal role,feature combination,towards efficient spl testing,current approach,efficient algorithm,software product line,variable software system,testing | Conference | 8 |
PageRank | References | Authors |
0.45 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthias Kowal | 1 | 73 | 6.07 |
| Sandro Schulze | 2 | 259 | 23.43 |
| Ina Schaefer | 3 | 1634 | 99.16 |