Abstract test cases (ATCs) have been widely used in practice, including in combinatorial testing and in software product line testing. When constructing a set of ATCs, due to limited testing resources in practice (e.g., in regression testing), test case prioritization (TCP) has been proposed to improve the testing quality, aiming at ordering test cases to increase the speed with which faults are detected. One intuitive and extensively studied TCP technique for ATCs is $\lambda$-wise Level-combination Coverage based Prioritization ($\lambda$LCP), a static, black-box prioritization technique that only uses the ATC information to guide the prioritization process. A challenge facing $\lambda$LCP, however, is the necessity for the selection of the fixed prioritization strength $\lambda$ before testing—testers need to choose an appropriate $\lambda$ value before testing begins. Choosing higher $\lambda$ values may improve the testing effectiveness of $\lambda$LCP (e.g., by finding faults faster), but may reduce the testing efficiency (by incurring additional prioritization costs). Conversely, choosing lower $\lambda$ values may improve the efficiency, but may also reduce the effectiveness. In this paper, we propose a new family of $\lambda$LCP techniques, Repeated Small-strength Level-combination Coverage-based Prioritization (RSLCP), that repeatedly achieves the full combination coverage at lower strengths. RSLCP maintains $\lambda$LCP's advantages of being static and black box, but avoids the challenge of prioritization strength selection. We have performed an empirical study involving five different versions of each of five C programs. Compared with $\lambda$LCP, and Incremental-strength LCP (ILCP), our results show that RSLCP could provide a good tradeoff between testing effectiveness and efficiency. Our results also show that RSLCP is more effective and efficient than two popular techniques of Similarity-based Prioritization (SP). In addition, the results of empirical studies also show that RSLCP can remain robust over multiple system releases.

中文翻译：

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使用重复的小强度级别组合覆盖的抽象测试用例优先级

摘要测试用例（ATC）在实践中得到了广泛的应用，包括组合测试和软件产品线测试。在构建ATC集合时，由于实践中测试资源有限（例如回归测试），为了提高测试质量，提出了测试用例优先级（TCP），旨在对测试用例进行排序以提高故障排除的速度。检测到。一种用于 ATC 的直观且广泛研究的 TCP 技术是$\lambda$-wise Level-combination 基于覆盖的优先级 ($\lambda$LCP），一种静态的黑盒优先排序技术，仅使用 ATC 信息来指导优先排序过程。面临的挑战$\lambda$然而，LCP 是选择固定优先级强度的必要性 $\lambda$ 测试前——测试人员需要选择合适的 $\lambda$测试开始前的值。选择更高$\lambda$ 值可能会提高测试的有效性 $\lambda$LCP（例如，通过更快地发现故障），但可能会降低测试效率（通过产生额外的优先级成本）。相反，选择较低的$\lambda$值可能会提高效率，但也可能会降低有效性。在本文中，我们提出了一个新的家族$\lambda$LCP技术， 重复小强度级别组合基于覆盖的优先级排序(RSLCP)，在较低强度下反复实现完全组合覆盖。RSLCP 维护$\lambda$LCP 具有静态和黑盒的优点，但避免了优先级强度选择的挑战。我们进行了一项实证研究，涉及五个 C 程序中每一个的五个不同版本。和....相比$\lambda$LCP，和 增量强度 LCP(ILCP)，我们的结果表明 RSLCP 可以在测试有效性和效率之间提供良好的权衡。我们的结果还表明，RSLCP 比两种流行的技术更有效和高效。基于相似性的优先级(SP)。此外，实证研究的结果还表明，RSLCP 可以在多个系统版本中保持稳健。