The Research of an Abstract Semantic Framework for Defect Detecting

Zhao Hong Yang; Qing Xiao; Yun Zhan Gong; Da Hai Jin; Ya Wen Wang

doi:10.4028/www.scientific.net/AMR.186.536

Paper Titles

Periodic Estimation of the 3-Arnold Transformation Modulo N
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Refinement Methodology for Modeling of Urban Road Traffic Networks
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A Method of Hyperbola Object Localization Based on Time Difference in Sensor Networks
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Analysis on Security Proof of Two Key Agreement Protocols
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The Research of an Abstract Semantic Framework for Defect Detecting
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Research on the Algorithm of Key Object Extraction in Motion Video Images
p.541

Flexible Job Shop Scheduling Multi-Objective Optimization Based on Improved Strength Pareto Evolutionary Algorithm
p.546

A Clustering Based Data Integration Algorithm in Wireless Sensor Networks
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Stochastic Simulation of Bus Traveling Time
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 186The Research of an Abstract Semantic Framework for...

The Research of an Abstract Semantic Framework for Defect Detecting

Abstract:

This paper proposes a non-relational abstract semantic framework. It uses interval set to represent the value of numerical variables and complete lattice to represent Boolean variables and reference variables. It presents the abstract computation method of basic expressions and the nodes of control flow graph. It uses function summaries to represent the context information of function call needed by defects detecting. Based on the results of abstract computation, it uses extended state machine to define defect patterns and proposes a path-sensitive method based on dataflow analysis to detect defects. It avoids the combination explosion of full path analysis by merging the conditions of identical property state at join points in the CFG. Practical test results show that the proposed methods have features of high efficiency, low false positive and low false negative.

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Periodical:

Advanced Materials Research (Volume 186)

Pages:

536-540

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.186.536

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Online since:

January 2011

Authors:

Zhao Hong Yang, Qing Xiao, Yun Zhan Gong, Da Hai Jin, Ya Wen Wang

Keywords:

Abstract Interpretation, Dataflow Analysis, Defect Detecting

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