• 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