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ACM SIGPLAN Notices
Article . 2001 . Peer-reviewed
License: https://www.acm.org/publications/policies/copyright_policy#Background
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https://dx.doi.org/10.1145/375...
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Slicing concurrent java programs

descriptionPublicationkeyboard_double_arrow_right Article 01 Apr 2001 English Publisher:Association for Computing Machinery (ACM)Journal:ACM SIGPLAN Notices, volume 36, pages 41-47 (issn: 0362-1340, eissn: 1558-1160, Copyright policy )
Authors: Zhenqiang Chen; Baowen Xu;

doi: 10.1145/375431.375420

Slicing concurrent java programs

Abstract

Program slicing is an important approach to testing, understanding and maintaining programs. The paper presents a slicing algorithm for concurrent Java programs. Because the execution process of concurrent programs is unpredictable, there are many problems to be solved when slicing. To slice concurrent Java programs, we present concurrent control flow graphs and concurrent program dependence graphs to representconcurrent Java programs. Based on these models, we design an efficient static slicing algorithm for concurrent Java programs. The algorithm may get more precise slices than previous approaches we know.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
36
Top 10%
Top 10%
Top 10%
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