Parametric and sliced causality

41Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Happen-before causal partial orders have been widely used in concurrent program verification and testing. This paper presents a parametric approach to happen-before causal partial orders. Existing variants of happen-before relations can be obtained as instances of the parametric framework. A novel causal partial order, called sliced causality, is then defined also as an instance of the parametric framework, which loosens the obvious but strict happen-before relation by considering static and dynamic dependence information about the program. Sliced causality has been implemented in a runtime predictive analysis tool for JAVA, named JPREDICTOR, and the evaluation results show that sliced causality can significantly improve the capability of concurrent verification and testing. © Springer-Verlag Berlin Heidelberg 2007.

Cite

CITATION STYLE

APA

Chen, F., & Roşu, G. (2007). Parametric and sliced causality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4590 LNCS, pp. 240–253). Springer Verlag. https://doi.org/10.1007/978-3-540-73368-3_27

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free