MicroRacer: Detecting Concurrency Bugs for Cloud Service Systems
Zhiling Deng, Juepeng Wang, Zhuangbin Chen

TL;DR
MicroRacer is a non-intrusive, automated framework that detects concurrency bugs in cloud microservice systems by analyzing runtime traces and validating suspicious concurrent operations, improving reliability.
Contribution
It introduces a novel, non-intrusive method for detecting concurrency bugs in microservice architectures using dynamic instrumentation and trace analysis.
Findings
Effectively detects concurrency bugs in open-source microservice benchmarks.
Accurately pinpoints concurrency issues with high efficiency.
Demonstrates robustness on replicated industrial bugs.
Abstract
Modern cloud applications delivering global services are often built on distributed systems with a microservice architecture. In such systems, end-to-end user requests traverse multiple different services and machines, exhibiting intricate interactions. Consequently, cloud service systems are vulnerable to concurrency bugs, which pose significant challenges to their reliability. Existing methods for concurrency bug detection often fall short due to their intrusive nature and inability to handle the architectural complexities of microservices. To address these limitations, we propose MicroRacer, a non-intrusive and automated framework for detecting concurrency bugs in such environments. By dynamically instrumenting widely-used libraries at runtime, MicroRacer collects detailed trace data without modifying the application code. Such data are utilized to analyze the happened-before…
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Taxonomy
TopicsSoftware System Performance and Reliability · Cloud Computing and Resource Management · Software Engineering Research
