Detail publikace

Fully Automated Shape Analysis Based on Forest Automata

Originální název

Fully Automated Shape Analysis Based on Forest Automata

Anglický název

Fully Automated Shape Analysis Based on Forest Automata

Jazyk

en

Originální abstrakt

Forest automata (FA) have recently been proposed as a tool for shape analysis of complex heap structures. FA encode sets of tree decompositions of heap graphs in the form of tuples of tree automata. In order to allow for representing complex heap graphs, the notion of FA allowed one to provide user-defined FA (called boxes) that encode repetitive graph patterns of shape graphs to be used as alphabet symbols of other, higher-level FA. In this paper, we propose a novel technique of automatically learning the FA to be used as boxes that avoids the need of providing them manually. Further, we propose a significant improvement of the automata abstraction used in the analysis. The result is an efficient, fully-automated analysis that can handle even as complex data structures as skip lists, with the performance comparable to state-of-the-art fully-automated tools based on separation logic, which, however, specialise in dealing with linked lists only.

Anglický abstrakt

Forest automata (FA) have recently been proposed as a tool for shape analysis of complex heap structures. FA encode sets of tree decompositions of heap graphs in the form of tuples of tree automata. In order to allow for representing complex heap graphs, the notion of FA allowed one to provide user-defined FA (called boxes) that encode repetitive graph patterns of shape graphs to be used as alphabet symbols of other, higher-level FA. In this paper, we propose a novel technique of automatically learning the FA to be used as boxes that avoids the need of providing them manually. Further, we propose a significant improvement of the automata abstraction used in the analysis. The result is an efficient, fully-automated analysis that can handle even as complex data structures as skip lists, with the performance comparable to state-of-the-art fully-automated tools based on separation logic, which, however, specialise in dealing with linked lists only.

BibTex


@inproceedings{BUT103488,
  author="Lukáš {Holík} and Ondřej {Lengál} and Adam {Rogalewicz} and Jiří {Šimáček} and Tomáš {Vojnar}",
  title="Fully Automated Shape Analysis Based on Forest Automata",
  annote="Forest automata (FA) have recently been proposed as a tool for shape analysis of
complex heap structures. FA encode sets of tree decompositions of heap graphs in
the form of tuples of tree automata. In order to allow for representing complex
heap graphs, the notion of FA allowed one to provide user-defined FA (called
boxes) that encode repetitive graph patterns of shape graphs to be used as
alphabet symbols of other, higher-level FA. In this paper, we propose a novel
technique of automatically learning the FA to be used as boxes that avoids the
need of providing them manually. Further, we propose a significant improvement of
the automata abstraction used in the analysis. The result is an efficient,
fully-automated analysis that can handle even as complex data structures as skip
lists, with the performance comparable to state-of-the-art fully-automated tools
based on separation logic, which, however, specialise in dealing with linked
lists only.",
  address="Springer Verlag",
  booktitle="Proceedings of CAV'13",
  chapter="103488",
  edition="NEUVEDEN",
  howpublished="print",
  institution="Springer Verlag",
  number="8044",
  year="2013",
  month="july",
  pages="740--755",
  publisher="Springer Verlag",
  type="conference paper"
}