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In this work, we propose the parallelisation of modular analyses. Modular analyses compute different parts of the analysis in isolation of one another, and therefore offer inherent opportunities for parallelisation that have not been explored so far. In addition, they can be used to develop a general class of analysers for dynamic, higher-order languages. We present a parallel variant of the worklist algorithm that is used to drive such modular analyses. To further speed up its convergence, we show how this algorithm can exploit the monotonicity of the analysis. Existing modular analyses can be parallelised without additional effort by instead employing this parallel worklist algorithm. We demonstrate this for ModF, an inter-procedural modular analysis, and for ModConc, an inter-process modular analysis. For ModConc, we reveal an additional opportunity to exploit even more parallelism in the analysis.
Our parallel worklist algorithm is implemented and integrated into MAF, a framework for modular program analysis.
Using a set of Scheme benchmarks for ModF, we usually observe speedups between 3x and 8x when using 4 workers, and speedups between 8x and 32x when using 16 workers.
For ModConc, we achieve a maximum speedup of 15x.
|Title of host publication||Proceedings of the 20th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2020)|
|Number of pages||12|
|Publication status||Published - 27 Sep 2020|
|Event||20th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM2020) - Adelaide, Australia|
Duration: 27 Sep 2020 → 28 Sep 2020
|Name||Proceedings - 20th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2020|
|Conference||20th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM2020)|
|Period||27/09/20 → 28/09/20|
- static analysis
- modular analysis
- dynamic languages
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1/11/19 → 31/10/21
1/09/19 → 3/03/22
1/10/17 → 30/09/21
- 1 Talk or presentation at a conference