2004•Concurrency and Computation Practice and ExperienceRequires access

A parallel algorithm for static slicing of concurrent programs

D. Goswami, Raghvendra Mall

Open publisher page 7 citations

Abstract

Abstract Slicing of concurrent programs is a compute‐intensive task. To speed up the slicing process, we have developed a parallel algorithm. For this purpose we used the concurrent control flow graph (CCFG) as the intermediate representation. We used a network of communicating processes to develop our parallel algorithm. We have implemented our parallel algorithm and the experimental results appear promising. Copyright © 2004 John Wiley & Sons, Ltd.

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What this paper is about

Abstract Slicing of concurrent programs is a compute‐intensive task. To speed up the slicing process, we have developed a parallel algorithm. For this purpose we used the concurrent control flow graph (CCFG) as the intermediate representation. We used a network of communicating processes to develop our parallel algorithm. We have implemented our parallel algorithm and the experimental results appear promising. Copyright © 2004 John Wiley & Sons, Ltd.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Abstract Slicing of concurrent programs is a compute‐intensive task. To speed up the slicing process, we have developed a parallel algorithm. For this purpose we used the concurrent control flow graph (CCFG) as the intermediate representation. We used a network of communicating processes to develop our parallel algorithm. We have implemented our parallel algorithm and the experimental results appear promising. Copyright © 2004 John Wiley & Sons, Ltd.

Key concepts: Slicing, Program slicing, Computer science, Parallel computing, Control flow graph, Task (project management), Control flow, Graph

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