论文标题
部分可观测时空混沌系统的无模型预测
Generalized Coverage Criteria for Combinatorial Sequence Testing
论文作者
论文摘要
我们提出了一种基于模型的新方法,用于测试系统,该方法将动作序列和断言作为测试向量。我们的解决方案包括一种量化测试质量的方法,一种基于我们建议的覆盖标准生成高质量测试套件的工具,以及评估风险的框架。对于测试质量,我们提出了一种指定对动作序列的广义覆盖标准的方法,该标准扩展了先前的方法。我们公开可用的工具演示了如何根据这些标准从测试计划中提取有效的测试套件。我们还提出了一种测量错误或风险概率的贝叶斯方法,并展示了该量化如何有助于在测试中的剥削和探索之间实现明智的平衡。最后,我们提供了经验评估,证明了我们工具在寻找错误,评估风险和实现覆盖范围的有效性。
We present a new model-based approach for testing systems that use sequences of actions and assertions as test vectors. Our solution includes a method for quantifying testing quality, a tool for generating high-quality test suites based on the coverage criteria we propose, and a framework for assessing risks. For testing quality, we propose a method that specifies generalized coverage criteria over sequences of actions, which extends previous approaches. Our publicly available tool demonstrates how to extract effective test suites from test plans based on these criteria. We also present a Bayesian approach for measuring the probabilities of bugs or risks, and show how this quantification can help achieve an informed balance between exploitation and exploration in testing. Finally, we provide an empirical evaluation demonstrating the effectiveness of our tool in finding bugs, assessing risks, and achieving coverage.