Hierarchical behavioral model for automatic runtime anomaly detection

Xiaomin Wan, Xiaoguang Mao
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Abstract

In order to detect runtime errors using program monitoring, specifications are necessary. This paper presents a novel model that describes hierarchical structure of program runtime behavior. The model is composed of elements with granularities from activity, object to action. By observing program behavior as it runs, we construct hierarchical view of program executions and extract behavioral models automatically. After that, we propose an automatic technique for runtime error detection for java programs with a preliminary experiment.
运行时异常自动检测的分层行为模型
为了使用程序监视检测运行时错误,规范是必要的。本文提出了一种描述程序运行时行为层次结构的新模型。该模型由从活动、对象到动作的粒度元素组成。通过观察程序运行时的行为,我们构建了程序执行的分层视图,并自动提取了行为模型。在此基础上,提出了一种java程序运行时错误自动检测技术,并进行了初步实验。
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