Justin Bradley | Searcharxiv

arXiv2026

Flaky Test Recognition when Testing CPSs Using Hybrid Models

Cyber-Physical Systems (CPSs) have many applications, ranging from simple thermostat systems to autonomous driving systems and medical devices. Like all systems, they need to function correctly. To this end, validation techniques such as testing that can effectively reveal faults are required. Also, CPSs usually operate in uncertain environments where various expected/unexpected events can affect their behaviors. These events together with timing and synchronization incidents may result in various/different CPS behaviors and may cause a CPS to pass a test under some conditions and fail it under others. Such test cases are called ``flaky'' test cases and we call the conditions that are responsible for them ``flaky conditions'' and call these behaviors ``flaky behaviors''. When test cases are flaky, testing results are unreliable. To achieve more reliable test results, engineers may attempt to recognize flaky test cases and remove them. In this work, beginning with a test case generation and execution technique called HyTest that we created previously, we integrate TReVa, a new technique that validates testing results provided by HyTest and FlaRe, a new technique that recognizes flaky test cases and flaky conditions using hybrid models during the early stages of CPS development in just one additional round of testing. We present the results of an empirical study evaluating the effectiveness of our new approach (which we call HyTestTF). Our results show that correctly differentiate flaky test cases from non-flaky test cases

cs.SE↗

arXiv2023

Test Case Generation and Test Oracle Support for Testing CPSs using Hybrid Models

Cyber-Physical Systems (CPSs) play a central role in the behavior of a wide range of autonomous physical systems such as medical devices, autonomous vehicles, and smart homes, many of which are safety-critical. CPSs are often specified iteratively as a sequence of models at different levels that can be tested via simulation systems at early stages of their development cycle. One such model is a hybrid automaton; these are used frequently for CPS applications and have the advantage of encapsulating both continuous and discrete CPS behaviors. When testing CPSs, engineers can take advantage of these models to generate test cases that target both types of these behaviors. Moreover, since these models are constructed early in the development process for CPSs, they allow test cases to be generated early in that process for those CPSs, even before simulation models of the CPSs have been designed. One challenge when testing CPSs is that these systems may operate differently even under an identically applied test scenario. In such cases, we cannot employ test oracles that use predetermined deterministic behaviors; instead, test oracles should consider sets of desired behaviors in order to determine whether the CPS has behaved appropriately. In this paper we present a test case generation technique, HYTEST, that generates test cases based on hybrid models, accompanied by appropriate test oracles, for use in testing CPSs early in their development cycle. To evaluate the effectiveness and efficiency of HYTEST, we conducted an empirical study in which we applied the technique to several CPSs and measured its ability to detect faults in those CPSs and the amount of time required to perform the testing process. The results of the study show that HYTEST was able to detect faults more effectively and efficiently than the baseline techniques we compare it to.

cs.SE↗