可配置系统实际测试的可靠性与效率平衡

Sabrina Souto, Marcelo d’Amorim, Rohit Gheyi
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引用次数: 31

摘要

测试可配置系统既重要又具有挑战性,因为可能隐藏错误的巨大配置空间。现有的测试这些系统的方法通常是昂贵的或不可靠的。本文提出了一种将启发式采样与符号搜索相结合的S-SPLat技术,以获得对构型空间探索的广度和深度。S-SPLat建立在SPLat之上,SPLat是我们以前开发的技术,它从测试中探索所有可到达的配置。与它的前身相比,S-SPLat为了效率而牺牲了稳健。我们在8个不同大小的软件产品线和一个大型可配置系统——GCC上评估了我们的技术。考虑到GCC的结果,S-SPLat能够重现我们之前在SPLat的研究中发现的所有五个错误,但速度要快得多,并且能够在最近的GCC版本中发现两个新错误。结果表明,与单一启发式相比,使用简单启发式的组合来驱动符号搜索是可取的。S-SPLat和我们的实验基础设施是公开的。
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Balancing Soundness and Efficiency for Practical Testing of Configurable Systems
Testing configurable systems is important and challenging due to the enormous space of configurations where errors can hide. Existing approaches to test these systems are often costly or unreliable. This paper proposes S-SPLat, a technique that combines heuristic sampling with symbolic search to obtain both breadth and depth in the exploration of the configuration space. S-SPLat builds on SPLat, our previously developed technique, that explores all reachable configurations from tests. In contrast to its predecessor, S-SPLat sacrifices soundness in favor of efficiency. We evaluated our technique on eight software product lines of various sizes and on a large configurable system – GCC. Considering the results for GCC, S-SPLat was able to reproduce all five bugs that we previously found in a previous study with SPLat but much faster and it was able to find two new bugs in a recent release of GCC. Results suggest that it is preferable to use a combination of simple heuristics to drive the symbolic search as opposed to a single heuristic. S-SPLat and our experimental infrastructure are publicly available.
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