Name
Abstract | ||
|---|---|---|
Quality assurance for product lines is often infeasible for each product separately. Instead, only a subset of all products (i.e., a sample) is considered during testing such that at least the coverage of certain feature interactions is guaranteed. While pair-wise interaction sampling only covers all interactions between two features, its generalization to t-wise interaction sampling ensures coverage for all interactions among t features. However, sampling large product lines poses a challenge, as today's algorithms tend to run out of memory, do not terminate, or produce samples, which are too large to be tested. To initiate a community effort, we provide a set of large real-world feature models with up-to 19 thousand features, which are supposed to be sampled. The performance of sampling approaches is evaluated based on the CPU time and memory consumed to retrieve a sample, the sample size for a given coverage (i.e. the value of t) and whether the sample achieves full t-wise coverage. A well-performing sampling algorithm achieves full t-wise coverage, while minimizing the other properties as best as possible.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3336294.3336322 | Proceedings of the 23rd International Systems and Software Product Line Conference - Volume A |
Keywords | DocType | ISBN |
product line testing, product sampling, real-world feature models, software product lines | Conference | 978-1-4503-7138-4 |
Citations | PageRank | References |
2 | 0.35 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Pett | 1 | 2 | 0.35 |
| Thomas Thüm | 2 | 1048 | 47.15 |
| Tobias Runge | 3 | 9 | 1.76 |
| Sebastian Krieter | 4 | 85 | 13.81 |
| Malte Lochau | 5 | 548 | 35.64 |
| Ina Schaefer | 6 | 1634 | 99.16 |