Algorithms for Interface Synthesis

(Invited Tutorial)
  • Dirk Beyer
  • Thomas A. Henzinger
  • Vasu Singh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4590)

Abstract

A temporal interface for a software component is a finite automaton that specifies the legal sequences of calls to functions that are provided by the component. We compare and evaluate three different algorithms for automatically extracting temporal interfaces from program code: (1) a game algorithm that computes the interface as a representation of the most general environment strategy to avoid a safety violation; (2) a learning algorithm that repeatedly queries the program to construct the minimal interface automaton; and (3) a CEGAR algorithm that iteratively refines an abstract interface hypothesis by adding relevant program variables. For comparison purposes, we present and implement the three algorithms in a unifying formal setting. While the three algorithms compute the same output and have similar worst-case complexities, their actual running times may differ considerably for a given input program. On the theoretical side, we provide for each of the three algorithms a family of input programs on which that algorithm outperforms the two alternatives. On the practical side, we evaluate the three algorithms experimentally on a variety of Java libraries.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alur, R., Cerny, P., Gupta, G., Madhusudan, P.: Synthesis of interface specifications for Java classes. In: Proc. POPL, pp. 98–109. ACM Press, New York (2005)Google Scholar
  2. 2.
    Angluin, D.: Learning regular sets from queries and counterexamples. Information and Computation 75, 87–106 (1987)MATHCrossRefGoogle Scholar
  3. 3.
    Clarke, E.M., Grumberg, O., Jha, S., Lu, Y., Veith, H.: Counterexample-guided abstraction refinement. In: Emerson, E.A., Sistla, A.P. (eds.) CAV 2000. LNCS, vol. 1855, pp. 154–169. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  4. 4.
    de Alfaro, L., Henzinger, T.A.: Interface automata. In: Proc. FSE, pp. 109–120. ACM Press, New York (2001)Google Scholar
  5. 5.
    Henzinger, T.A., Jhala, R., Majumdar, R.: Permissive interfaces. In: Proc. FSE, pp. 31–40. ACM Press, New York (2005)Google Scholar
  6. 6.
    Hopcroft, J.E.: An n·logn algorithm for minimizing states in a finite automaton. In: Proc. Theory of Machines and Computations, pp. 189–196. Acad. Press, San Diego (1971)Google Scholar
  7. 7.
    Rivest, R.L., Schapire, R.E.: Inference of finite automata using homing sequences. Information and Computation 103, 299–347 (1993)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Dirk Beyer
    • 1
  • Thomas A. Henzinger
    • 2
  • Vasu Singh
    • 2
  1. 1.Simon Fraser University, B.C.Canada
  2. 2.EPFLSwitzerland

Personalised recommendations