Software systems are deployed in environments that keep changing over time. They should therefore adapt to changing conditions to meet their requirements. The satisfaction rate of these requirements depends on the rate at which adverse conditions prevent their satisfaction. Obstacle analysis is a goal-oriented form of risk analysis for requirements engineering (RE), whereby obstacles to system goals are identified, assessed, and resolved through countermeasures. The selection of effective countermeasures relies on environment assumptions and on the assessed likelihood and criticality of the corresponding obstacles. Those various factors estimated at RE time may, however, evolve at system runtime. To meet the system’s goals under changing conditions, this article proposes to defer obstacle resolution to system runtime. Techniques are presented for monitoring obstacle satisfaction rates; deciding when adaptation should be triggered; and adapting the system on-the-fly to countermeasures that are more effective. The approach relies on a model where goals and obstacles are refined and specified in a probabilistic linear temporal logic. The techniques allow for monitoring the satisfaction rate of probabilistic leaf obstacles; determining the severity of obstacle consequences on goal satisfaction rates computed from the monitored obstacle satisfaction rates; and shifting to countermeasures that better meet the required goal satisfaction rates. Our approach is evaluated on fragments of an ambulance dispatching system.

中文翻译：

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运行时监控和解决系统目标的概率障碍

软件系统部署在随时间不断变化的环境中。因此，他们应该适应不断变化的条件以满足他们的要求。这些要求的满足率取决于不利条件妨碍满足的速度。障碍分析是针对需求工程 (RE) 的风险分析的一种面向目标的形式，其中通过对策来识别、评估和解决系统目标的障碍。有效对策的选择依赖于环境假设以及评估的相应障碍的可能性和关键性。然而，在 RE 时估计的各种因素可能会在系统运行时演变。为了在不断变化的条件下满足系统的目标，本文提出将障碍物的解决推迟到系统运行时。提出了监测障碍物满足率的技术；决定何时触发适应；并即时调整系统以应对更有效的对策。该方法依赖于一个模型，其中目标和障碍在概率线性时间逻辑中被细化和指定。该技术允许监测概率叶障碍物的满意度；根据监测的障碍物满足率，确定障碍物后果对目标满足率的严重程度；并转向更好地满足所需目标满足率的对策。我们的方法是在救护车调度系统的片段上进行评估的。并即时调整系统以应对更有效的对策。该方法依赖于一个模型，其中目标和障碍在概率线性时间逻辑中被细化和指定。该技术允许监测概率叶障碍物的满意度；根据监测的障碍物满足率，确定障碍物后果对目标满足率的严重程度；并转向更好地满足所需目标满足率的对策。我们的方法是在救护车调度系统的片段上进行评估的。并即时调整系统以应对更有效的对策。该方法依赖于一个模型，其中目标和障碍在概率线性时间逻辑中被细化和指定。该技术允许监测概率叶障碍物的满意度；根据监测的障碍物满足率，确定障碍物后果对目标满足率的严重程度；并转向更好地满足所需目标满足率的对策。我们的方法是在救护车调度系统的片段上进行评估的。根据监测的障碍物满足率，确定障碍物后果对目标满足率的严重程度；并转向更好地满足所需目标满足率的对策。我们的方法是在救护车调度系统的片段上进行评估的。根据监测的障碍物满足率，确定障碍物后果对目标满足率的严重程度；并转向更好地满足所需目标满足率的对策。我们的方法是在救护车调度系统的片段上进行评估的。