International Symposium on Software Testing and Analysis

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Author

B. Xin and X. Zhang

Entry type

conference

Abstract

Capturing dynamic control dependence is critical for many dynamic program analysis such as dynamic slicing, dynamic information flow, and data lineage computation. Existing algorithms are mostly a simple runtime translation of the static definition, which fails to capture certain dynamic properties by its nature, leading to inefficiency. In this paper, we propose a novel online detection technique for dynamic control dependence. The technique is based upon a new definition, which is equivalent to the existing one in the intraprocedural case but it enables an efficient detection algorithm. The new algorithm naturally and efficiently handles interprocedural dynamic control dependence even in presence of irregular control flow. Our evaluation shows that the detection algorithm slows down program execution by a factor of 2.57, which is 2.54 times faster than the existing algorithm that was used in prior work.

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Date

2007 – 07

Key alpha

software engineering, program analysis, security

Affiliation

Purdue

Publication Date

2007-07-01

Keywords

dynamic control dependence, dynamic analysis

Subject

dynamic information flow. program dependence. control dependence. program execution.

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@Conference{ software engineering, program analysis, security,
	title = "International Symposium on Software Testing and Analysis",
	author = "B. Xin and X. Zhang",
	year = "2007",
	month = "07",
	abstract = "Capturing dynamic control dependence is critical for many dynamic program analysis such as dynamic slicing, dynamic information flow, and data lineage computation. Existing algorithms are mostly a simple runtime translation of the static definition, which fails to capture certain dynamic properties by its nature, leading to inefficiency. In this paper, we propose a novel online detection technique
for dynamic control dependence. The technique is based upon a new definition, which is equivalent to the existing one in the intraprocedural case but it enables an efficient detection algorithm. The new algorithm naturally and efficiently handles interprocedural dynamic control dependence even in presence of irregular control flow. Our evaluation shows that the detection algorithm slows down program execution by a factor of 2.57, which is 2.54 times
faster than the existing algorithm that was used in prior work.",
	affiliation = "Purdue",
	keywords = "dynamic control dependence,  dynamic analysis",
	subject = "dynamic information flow.
program dependence.
control dependence.
program execution.",
}