MC/DC Test Cases Generation Based on BDDs
Chapter, Peer reviewed
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Date
2021Metadata
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Original version
Ahishakiye, F., Requeno Jarabo, J. I., Kristensen, L. M., & Stolz, V. (2021). MC/DC test cases generation based on BDDs. In S. Qin, J. Woodcock, & W. Zhang (Eds.), SETTA2021: 7th International Symposium on Dependable Software Engineering: Theories, Tools, and Applications (pp. 178-197). Springer International Publishing. 10.1007/978-3-030-91265-9_10Abstract
We present a greedy approach to test-cases selection for single decisions to achieve MC/DC-coverage of their Boolean conditions. Our heuristics take into account “don’t care” inputs through three-valued truth values that we obtain through a compact representation via reduced-ordered binary decision diagrams (roBDDs). In contrast to an exhaustive, resource-consuming search for an optimal solution, our approach quickly gives frequently either optimal results, or otherwise produces “good enough” results (close to the optimal size) with little complexity. Users obtain different—possibly better—solutions by permuting the order of conditions when constructing the BDD, allowing them to identify the best solutions within a given time budget. We compare variations on metrics that guide the heuristics.
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This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-030-91265-9_10