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P2 DCatch

DCatch：分布式并发缺陷检测
ASPLOS Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems2017匹配度 1/10 · 该论文研究分布式并发缺陷的动态检测（基于happens-before关系的运行时分析），属于软件测试与调试领域，与用户关注的PL与AI交叉（静态分析、Agentic程序、LLM改进分析）、浮点程序分析、贝叶斯程序分析等核心方向无关。引用 65 inbox
Haopeng Liu, Guangpu Li, Jeffrey F. Lukman, Jiaxin Li, Shan Lu, Haryadi S. Gunawi, Chen Tian
测试、调试与修复并发、并行与内存模型
crossref: 2026-09-12dblp: 2026-09-12

AI 速览

一句话：提出 DCatch，通过分析正确执行中的 happens-before 关系来预测分布式并发缺陷。

大数据与云计算时代，分布式系统可靠性至关重要，但分布式并发缺陷（DCbug）广泛存在且难以触发。论文提出 DCatch，通过分析分布式系统的正确执行来预测 DCbug：设计一组 happens-before 规则，覆盖真实分布式云系统中多种通信与并发机制；构建运行时追踪与迹分析工具，识别并发冲突的内存访问；并设计误报剪枝与缺陷触发工具。作者在 Cassandra、Hadoop MapReduce、HBase 和 ZooKeeper 四个代表性开源系统上评估，监控七种工作负载的正确执行，共报告 32 个 DCbug，其中 20 个确实有害。

问题
分布式云系统中的分布式并发缺陷（DCbug）隐藏在巨大状态空间中，依赖计算与通信时序非确定性地暴露，缺乏有效检测手段。
方法
设计覆盖真实分布式云系统通信与并发机制的 happens-before 规则，并结合运行时追踪、迹分析、误报剪枝和缺陷触发工具来预测 DCbug。
评估
在 Cassandra、Hadoop MapReduce、HBase 和 ZooKeeper 上监控七种工作负载的正确执行，报告 32 个 DCbug，其中 20 个真正有害。
原文摘要（Abstract）

In big data and cloud computing era, reliability of distributed systems is extremely important. Unfortunately, distributed concurrency bugs, referred to as DCbugs, widely exist. They hide in the large state space of distributed cloud systems and manifest non-deterministically depending on the timing of distributed computation and communication. Effective techniques to detect DCbugs are desired. This paper presents a pilot solution, DCatch, in the world of DCbug detection. DCatch predicts DCbugs by analyzing correct execution of distributed systems. To build DCatch, we design a set of happens-before rules that model a wide variety of communication and concurrency mechanisms in real-world distributed cloud systems. We then build runtime tracing and trace analysis tools to effectively identify concurrent conflicting memory accesses in these systems. Finally, we design tools to help prune false positives and trigger DCbugs. We have evaluated DCatch on four representative open-source distributed cloud systems, Cassandra, Hadoop MapReduce, HBase, and ZooKeeper. By monitoring correct execution of seven workloads on these systems, DCatch reports 32 DCbugs, with 20 of them being truly harmful.

链接与引用

DOI 原文 · DBLP

BibTeX 
@inproceedings{LiuLLLLGT17,
  title = {DCatch},
  author = {Haopeng Liu and Guangpu Li and Jeffrey F. Lukman and Jiaxin Li and Shan Lu and Haryadi S. Gunawi and Chen Tian},
  booktitle = {ASPLOS},
  year = {2017},
  doi = {10.1145/3037697.3037735}
}