A Parallel Worklist Algorithm for Modular Analyses

Es, Noah Van; Stiévenart, Quentin; Plas, Jens Van der; Roover, Coen De

doi:10.1109/scam51674.2020.00006

Cited by 2 publications

(1 citation statement)

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“…MAF also includes other sequential worklist algorithms, e.g., using a FIFO or priority-based ordering. It also includes a parallel worklist algorithm, where multiple threads analyse components in the worklist in parallel [12].…”

Section: B the Worklist Traitsmentioning

confidence: 99%

MAF: A Framework for Modular Static Analysis of Higher-Order Languages

Plas

Stiévenart

et al. 2020

2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM)

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A modular static analysis decomposes a program's analysis into analyses of its parts, or components. An intercomponent analysis instructs an intra-component analysis to analyse each component independently of the others. Additional analyses are scheduled for newly discovered components, and for dependent components that need to account for newly discovered component information. Modular static analyses are scalable, can be tuned to a high precision, and support the analysis of programs that are highly dynamic, featuring e.g., higher-order functions or dynamically allocated processes.In this paper, we present the engineering aspects of MAF, a static analysis framework for implementing modular analyses for higher-order languages. For any such modular analysis, the framework provides a reusable inter-component analysis and it suffices to implement its intra-component analysis. The intracomponent analysis can be composed from several interdependent and reusable Scala traits. This design facilitates changing the analysed language, as well as the analysis precision with minimal effort. We illustrate the use of MAF through its instantiation for several different analyses of Scheme programs.

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Section: B the Worklist Traitsmentioning

confidence: 99%