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Concurrent Software Fine-Coarse-Grained Automatic Modeling Method for Algorithm Error Detection

机译:并发软件精细粗粒颗粒算法错误检测自动建模方法

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Concurrent software state space explodes, which makes algorithm error detection difficult. This paper proposes a fine-coarse-grained automatic modeling method. Based on the JAVA concurrent program, we generate the HCPN (Hierarchical Coloured Petri Net) fine-coarse-grained model that in accordance with the behavior of the source program automatically. The goal is to detect the algorithm errors in the program through the model checking technology. We complete the modeling of interactive, property-related and specific structure statements through fine-grained method and complete the modeling of other statements through coarse-grained method. Avoid the state space explosion effectively under the premise of retaining the interaction behavior and the property-related behavior execution path. This paper verifies the effect of fine-coarse-grained automatic modeling method by comparing and analyzing the experimental results.
机译:并发软件状态空间爆炸,这使得算法错误检测困难。本文提出了一种细粗粒粒度的自动建模方法。基于Java并发程序,我们生成HCPN(分层彩色Petri Net)细粗粒模型,根据源程序自动的行为。目标是通过模型检查技术检测程序中的算法错误。我们通过细粒度方法完成交互式,物业相关和特定结构陈述的建模,通过粗粒法完成其他陈述的建模。在保留交互行为和属性相关行为执行路径的前提下,有效地避免状态空间爆炸。本文通过比较和分析实验结果来验证细粗粒自动建模方法的影响。

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