期刊
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
卷 48, 期 12, 页码 4733-4761出版社
IEEE COMPUTER SOC
DOI: 10.1109/TSE.2021.3124795
关键词
Distributed system; program analysis; dependence analysis; dynamic analysis
资金
- U.S. National Science Foundation(NSF) [CCF-1936522]
- U.S. Department ofEnergy (DOE) [379101]
This paper presents the D(2)ABS framework for dynamic dependence analysis of distributed programs, offering a trade-off between efficiency and precision. By ordering events and utilizing message-passing semantics, the framework can compute method-level dependencies across different processes.
As modern software systems are increasingly developed for running in distributed environments, it is crucial to provide fundamental techniques such as dependence analysis for checking, diagnosing, and evolving those systems. However, traditional dependence analysis is either inapplicable or of very limited utility for distributed programs due to the decoupled components of these programs which run in concurrent processes at physically separated machines. Motivated by the need for dependence analysis of distributed software and the diverse cost-effectiveness needs of dependence-based applications, this paper presents D(2)ABS, a framework of dynamic dependence analysis for distributed programs. By partially ordering distributed method execution events and inferring causality from the ordered events, D(2)ABS computes method-level dependencies both within and across process boundaries. Further, by exploiting message-passing semantics across processes, and incorporating static dependencies and statement coverage within individual components, D(2)ABS offers three additional instantiations that trade efficiency for better precision. We present the design of the D(2)ABS framework and evaluate the four instantiations of D(2)ABS on distributed systems of various architectures and scales using our implementation for Java. Our empirical results show that D(2)ABS is significantly more effective than existing options while offering varying levels of cost-effectiveness tradeoffs. As our framework essentially computes whole-system run-time dependencies, it naturally empowers a range of other dependence-based applications.
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