Hybrid partial order reduction with under-approximate dynamic points-to and determinacy information

P. Parízek
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Abstract

Verification techniques for concurrent systems are often based on systematic state space traversal. An important piece of such techniques is partial order reduction (POR). Many algorithms of POR have been already developed, each having specific advantages and drawbacks. For example, fully dynamic POR is very precise but it has to check every pair of visible actions to detect all interferences. Approaches involving static analysis can exploit knowledge about future behavior of program threads, but they have limited precision. We present a new hybrid POR algorithm that builds upon (i) dynamic POR and (ii) hybrid field access analysis that combines static analysis with data taken on-the-fly from dynamic program states. The key feature of our algorithm is usage of under-approximate dynamic points-to and determinacy information, which is gradually refined during a run of the state space traversal procedure. Knowledge of dynamic points-to sets for local variables improves precision of the field access analysis. Our experimental results show that the proposed hybrid POR achieves better performance than existing techniques on selected benchmarks, and it enables fast detection of concurrency errors.
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基于欠近似动态点和确定性信息的混合偏阶约简
并发系统的验证技术通常基于系统状态空间遍历。这种技术的一个重要部分是偏序约简(POR)。目前已经开发了许多POR算法,每种算法都有其特定的优点和缺点。例如,全动态POR非常精确,但它必须检查每一对可见动作以检测所有干扰。涉及静态分析的方法可以利用有关程序线程未来行为的知识,但它们的精度有限。我们提出了一种新的混合POR算法,该算法建立在(i)动态POR和(ii)混合现场访问分析的基础上,该分析将静态分析与动态程序状态的实时数据相结合。该算法的主要特点是使用了欠近似的动态点和确定性信息,并在状态空间遍历过程中逐步改进。局部变量的动态点到集的知识提高了现场访问分析的精度。我们的实验结果表明,所提出的混合POR在选定的基准测试上取得了比现有技术更好的性能,并且能够快速检测并发错误。
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