Chronos: Finding Timeout Bugs in Practical Distributed Systems by Deep-Priority Fuzzing with Transient Delay
Yuanliang Chen, Fuchen Ma, Yuanhang Zhou, Ming Gu, Qing Liao, Yu Jiang
Abstract
Delays are inevitable in complex distributed environments. Timeout mechanisms are commonly used to handle unexpected failures in distributed systems. However, incorrect timeout handling or implementation errors in timeout mechanisms can lead to system hang-ups or crashes. Such timeout bugs may be crucial and pose a significant threat to the availability and security of distributed systems.In this work, we introduce Chronos, a general testing framework for automatically detecting timeout bugs in distributed systems with deep-priority transient delays. First, we propose general runtime delayed libraries that dynamically inject fine-grained delays in a Distributed System Under Test (DSUT). To effectively trigger delays and constantly explore timeout bugs in deep paths, Chronos harnesses a deep-priority guided fuzzing that dynamically generates high-quality delay sequences in the runtime. Then, Chronos utilizes transient delays to eliminate the time overhead caused by actual delays and accelerate the test process. We implemented and evaluated Chronos on four widely used distributed systems, including ZooKeeper, MySQL-Cluster, HDFS, and Go-Ethereum. Compared with the state-of-the-art techniques, Random, Brute-Force, and Coverage-Guided fault injection, Chronos covers 26.40%, 21.69%, and 15.14% more timeout mechanism logic, respectively. Furthermore, Chronos has detected 27 timeout bugs in these real-world applications, which have been repaired by the corresponding maintainers.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5dca6a0c-50a4-4ccd-b635-d6f4fb670185Cited by top-tier papers8
- RL-Watchdog: A Fast and Predictable SSD Liveness Watchdog on Storage SystemsJinyong Ha, Sangjin Lee, Heon Young Yeom, Yongseok SonUSENIX ATC 2024 · 10 citations
- CAFault: Enhance Fault Injection Technique in Practical Distributed Systems via Abundant Fault-Dependent ConfigurationsYuanliang Chen, Fuchen Ma, Yuanhang Zhou, Zhen Yan et al.USENIX ATC 2025 · 7 citations
- Understanding and Detecting SQL Function Bugs: Using Simple Boundary Arguments to Trigger Hundreds of DBMS BugsJingzhou Fu, Jie Liang, Zhiyong Wu, Yanyang Zhao et al.EuroSys 2025 · 6 citations
- Understanding and Detecting Fail-Slow Hardware Failure Bugs in Cloud SystemsGen Dong, Yu Hua, Yongle Zhang, Zhangyu Chen et al.USENIX ATC 2025 · 6 citations
- UpFuzz: Detecting Data Format Incompatibility Bugs during Distributed Storage System UpgradeKe Han, P. C. Sruthi, Yayu Wang, Yaoxu Song et al.NSDI 2026 · 3 citations
Builds on12
- Plundervolt: Software-based Fault Injection Attacks against Intel SGXKit Murdock, David F. Oswald, Flavio D. Garcia, Jo Van Bulck et al.S&P 2020 · 369 citations
- Testing Database Engines via Pivoted Query SynthesisManuel Rigger, Zhendong SuOSDI 2020 · 150 citations
- EnFuzz: Ensemble Fuzzing with Seed Synchronization among Diverse FuzzersYuanliang Chen, Yu Jiang, Fuchen Ma, Jie Liang et al.USENIX Security 2019 · 139 citations
- HEALER: Relation Learning Guided Kernel FuzzingHao Sun, Yuheng Shen, Cong Wang, Jianzhong Liu et al.SOSP 2021 · 59 citations
- Perseus: A Fail-Slow Detection Framework for Cloud Storage SystemsRuiming Lu, Erci Xu, Yiming Zhang, Fengyi Zhu et al.FAST 2023 · 31 citations
Related papers
- Coverage Guided Fault Injection for Cloud SystemsYu Gao, Wensheng Dou, Dong Wang, Wenhan Feng et al.ICSE 2023 · 13 citations
- ECFuzz: Effective Configuration Fuzzing for Large-Scale SystemsJunqiang Li, Senyi Li, Keyao Li, Falin Luo et al.ICSE 2024 · 12 citations
- Blackbox Fuzzing of Distributed Systems with Multi-Dimensional Inputs and Symmetry-Based Feedback PruningYonghao Zou, Jia-Ju Bai, Zu-Ming Jiang, Ming Zhao et al.NDSS 2025
- Fizzle: A Framework for Deterministic and Reproducible Network FuzzingNathaniel Bennett, Tyler Tucker, Carson Stillman, William Enck et al.S&P 2026 · 1 citation
- LOKI: State-Aware Fuzzing Framework for the Implementation of Blockchain Consensus ProtocolsFuchen Ma, Yuanliang Chen, Meng Ren, Yuanhang Zhou et al.NDSS 2023
