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Dependence Guided Symbolic Execution

delete2017-03-01
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OA
AI
H
Haijun Wang *
刘烃 cover
刘烃 (Ting Liu)
X
Xiaohong Guan
C
Chao Shen
Q
Qinghua Zheng
杨
杨子江 (Zijiang Yang)
DOI:10.1109/TSE.2016.2584063delete
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Abstract

Abstract

En 中文
Symbolic execution is a powerful technique for systematically exploring the paths of a program and generating the corresponding test inputs. However, its practical usage is often limited by the path explosion problem, that is, the number of explored paths usually grows exponentially with the increase of program size. In this paper, we argue that for the purpose of fault detection it is not necessary to systematically explore the paths, and propose a new symbolic execution approach to mitigate the path explosion problem by predicting and eliminating the redundant paths based on symbolic value. Our approach can achieve the equivalent fault detection capability as traditional symbolic execution without exhaustive path exploration. In addition, we develop a practical implementation called Dependence Guided Symbolic Execution (DGSE) to soundly approximate our approach. Through exploiting program dependence, DGSE can predict and eliminate the redundant paths at a reasonable computational cost. Our empirical study shows that the redundant paths are abundant and widespread in a program. Compared with traditional symbolic execution, DGSE only explores 6.96 to 96.57 percent of the paths and achieves a speedup of 1.02 x to 49.56 x. We have released our tool and the benchmarks used to evaluate DGSE.
Keywords:
Symbolic execution
path coverage
program dependence
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Journal

IEEE Transactions on Software Engineering cover
IEEE Transactions on Software Engineering
IF:
5.6
Papers:
2.9K
Citations:
1.1W

Organization

X
xi'an jiaotong university
Scholars:
9.3W
Papers: 6.7W
Citations: 75
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