Self-adaptive systems have to implement adaptation policies described by sets of rules that express how the components are reconfigured within the system, the priority of a given reconfiguration to happen, when a given (sequence of) event(s) occurs, and when specific conditions on the system state are satisfied. However, when this priority is given by a fuzzy value (e.g., high, medium, low) depending on external and internal events, it has to be implemented inside the software with particular implementation choices made. This paper is dedicated to the validation of adaptation policies, using a model-based testing approach and a verdict establishment that is based on both the runtime verification of temporal properties, and the detection of inconsistencies between the adaptation policy and the reconfigurations implemented in the self-adaptive system. We propose means to establish a test verdict based on the respect of the adaptation policy by the implementation, along with coverage measures of the rules. This provides interesting feedback on the adaptation policy rules, allowing to detect reconfigurations that should not have occurred, high-priority reconfigurations that are never triggered, or low-priority reconfigurations that are too frequently executed, potential inconsistencies in the rules, or wrong interpretation of priorities. The test verdict is made based on the analysis of the execution traces of the system, which is stimulated using a usage model that describes the probabilities of external events to occur. An experiment, performed on a vehicular ad-hoc network of autonomous vehicles, illustrates the interest of the approach.

中文翻译：

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测试软件组件的适配策略

自适应系统必须实施由一组规则描述的适应策略，这些规则表达了如何在系统内重新配置组件、给定重新配置发生的优先级、给定（序列）事件发生的时间以及特定的时间满足系统状态的条件。然而，当这个优先级由取决于外部和内部事件的模糊值（例如，高、中、低）给出时，它必须在软件内部实现，并做出特定的实现选择。本文致力于验证适应策略，使用基于模型的测试方法和基于时间属性的运行时验证的判定建立，以及自适应策略与自适应系统中实现的重新配置之间的不一致的检测。我们提出了基于实施对适应政策的尊重以及规则的覆盖范围来建立测试判决的方法。这为适应策略规则提供了有趣的反馈，允许检测不应该发生的重新配置、从未触发的高优先级重新配置或过于频繁执行的低优先级重新配置、规则中的潜在不一致或错误解释优先事项。测试判定是基于对系统执行轨迹的分析做出的，该轨迹是使用描述外部事件发生概率的使用模型来激发的。一个实验，