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Automated Generation of Model-Based Constraints for Common Multi-core and Real-Time Applications Using Execution Tracing

机译:使用执行跟踪自动生成基于模型的基于模型的限制和实时应用程序

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摘要

Analyzing the runtime of a real-time application is particularly difficult with interferences from concurrently running processes. Low-overhead tracing is usually the most reliable tool to understand and check the behavior of such applications. In previous work, the automatic detection of common real-time problems was proposed, using models and constraints over the behavior of the application and operating system. Such a model automates system verification, alleviating the need for a thorough and deep understanding of all the system internals, and reduces drastically the time needed to find root causes for problems. Nevertheless, coming up with a model is not trivial. In this paper, we present a way to automate building a model of the process with constraints, based on user-space and kernel execution traces. Recurrent event sequences are used to build an approximate model of the behavior, and typical timings are used for setting up tentative constraints. The resulting model can then be refined as needed through user intervention. Our algorithms and their scalability have been tested and the experimental results show that our approach allows to build a model to automatically detect common problems in applications, with a relatively modest analysis cost.
机译:分析实时应用程序的运行时间尤其困难,并且来自同时运行进程的干扰。低开销跟踪通常是最可靠的工具,可以理解和检查此类应用程序的行为。在以前的工作中,提出了在应用程序和操作系统的行为上使用模型和约束来自动检测常见的实时问题。这样的模型自动化系统验证,减轻了对所有系统内部内部的彻底和深刻了解的需要,并急剧减少了寻找问题的根源所需的时间。尽管如此,与模型出现并不琐碎。在本文中,我们提出了一种方法来自动构建具有约束的过程模型,基于用户空间和内核执行迹线。经常性事件序列用于构建行为的近似模型,典型的定时用于设置临时约束。然后可以通过用户干预根据需要改进所得到的模型。我们的算法及其可扩展性已经过测试,实验结果表明,我们的方法允许构建模型,以自动检测应用中的常见问题,具有相对较为谦逊的分析成本。

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