We investigate how to execute a unit test for all products of a product line without generating each product in isolation in a brute-force fashion. Learning from variability-aware analyses, we (a) design and implement a variability-aware interpreter and, alternatively, (b) reencode variability of the product line to simulate the test cases with a model checker. The interpreter internally reasons about variability, executing paths not affected by variability only once for the whole product line. The model checker achieves similar results by reusing powerful off-the-shelf analyses. We experimented with a prototype implementation for each strategy. We compare both strategies and discuss trade-offs and future directions. In the long run, we aim at finding an efficient testing approach that can be applied to entire product lines with millions of products.
For example, REF presented a method to reduce the efforts of executing a test over the whole set of products encoded in a product line.
Toward variability-aware testing
FOSD '12
Computer Science