Coverage Guided Fault Injection for Cloud Systems

Gao, Yu; Dou, Wensheng; Wang, Dong; Feng, Wenhan; Wei, Jun; Zhong, Hua; Huang, Tao

doi:10.1109/icse48619.2023.00186

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2024

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Cited by 3 publications

References 26 publications

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Chronos: Finding Timeout Bugs in Practical Distributed Systems by Deep-Priority Fuzzing with Transient Delay

Chen,

Ma,

Zhou

et al. 2024

2024 IEEE Symposium on Security and Privacy (SP)

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Chronos: Finding Timeout Bugs in Practical Distributed Systems by Deep-Priority Fuzzing with Transient Delay

Chen,

Ma,

Zhou

et al. 2024

2024 IEEE Symposium on Security and Privacy (SP)

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SandTable: Scalable Distributed System Model Checking with Specification-Level State Exploration

Tang,

Sun,

Huang

et al. 2024

Proceedings of the Nineteenth European Conference on Computer Systems

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Reward Augmentation in Reinforcement Learning for Testing Distributed Systems

Borgarelli,

Enea,

Majumdar

et al. 2024

Proc. ACM Program. Lang.

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Bugs in popular distributed protocol implementations have been the source of many downtimes in popular internet services. We describe a randomized testing approach for distributed protocol implementations based on reinforcement learning. Since the natural reward structure is very sparse, the key to successful exploration in reinforcement learning is reward augmentation. We show two different techniques that build on one another. First, we provide a decaying exploration bonus based on the discovery of new states---the reward decays as the same state is visited multiple times. The exploration bonus captures the intuition from coverage-guided fuzzing of prioritizing new coverage points; in contrast to other schemes, we show that taking the maximum of the bonus and the Q-value leads to more effective exploration. Second, we provide waypoints to the algorithm as a sequence of predicates that capture interesting semantic scenarios. Waypoints exploit designer insight about the protocol and guide the exploration to "interesting" parts of the state space. Our reward structure ensures that new episodes can reliably get to deep interesting states even without execution caching. We have implemented our algorithm in Go. Our evaluation on three large benchmarks (RedisRaft, Etcd, and RSL) shows that our algorithm can significantly outperform baseline approaches in terms of coverage and bug finding.

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Coverage Guided Fault Injection for Cloud Systems

Cited by 3 publications

References 26 publications

Chronos: Finding Timeout Bugs in Practical Distributed Systems by Deep-Priority Fuzzing with Transient Delay

Chronos: Finding Timeout Bugs in Practical Distributed Systems by Deep-Priority Fuzzing with Transient Delay

SandTable: Scalable Distributed System Model Checking with Specification-Level State Exploration

Reward Augmentation in Reinforcement Learning for Testing Distributed Systems

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