DocumentCode :
1383153
Title :
Program Behavior Discovery and Verification: A Graph Grammar Approach
Author :
Zhao, Chunying ; Kong, Jun ; Zhang, Kang
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas at Dallas, Richardson, TX, USA
Volume :
36
Issue :
3
fYear :
2010
Firstpage :
431
Lastpage :
448
Abstract :
Discovering program behaviors and functionalities can ease program comprehension and verification. Existing program analysis approaches have used text mining algorithms to infer behavior patterns or formal models from program execution. When one tries to identify the hierarchical composition of a program behavior at different abstraction levels, textual descriptions are not informative and expressive enough. To address this, we present a semi-automatic graph grammar approach to retrieving the hierarchical structure of the program behavior. The hierarchical structure is built on recurring substructures in a bottom-up fashion. We formulate the behavior discovery and verification problem as a graph grammar induction and parsing problem, i.e., automatically iteratively mining qualified patterns and then constructing graph rewriting rules. Furthermore, using the induced grammar to parse the behavioral structure of a new program could verify if the program has the same behavioral properties specified by the grammar.
Keywords :
data mining; graph grammars; program verification; behavior patterns; formal models; graph rewriting rules; mining qualified patterns; program behavior discovery; program behavior verification; program comprehension; program execution; semi-automatic graph grammar approach; text mining algorithms; Visual language; graph grammar induction; program comprehension; reengineering.;
fLanguage :
English
Journal_Title :
Software Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-5589
Type :
jour
DOI :
10.1109/TSE.2010.3
Filename :
5383371
Link To Document :
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