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Automating Coinduction with Case Analysis

  • Eugen-Ioan Goriac
  • Dorel Lucanu
  • Grigore Roşu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6447)

Abstract

Coinduction is a major technique employed to prove behavioral properties of systems, such as behavioral equivalence. Its automation is highly desirable, despite the fact that most behavioral problems are \(\Pi_2^0\)-complete. Circular coinduction, which is at the core of the CIRC prover, automates coinduction by systematically deriving new goals and proving existing ones until, hopefully, all goals are proved. Motivated by practical examples, circular coinduction and CIRC have been recently extended with several features, such as special contexts, generalization and simplification. Unfortunately, none of these extensions eliminates the need for case analysis and, consequently, there are still many natural behavioral properties that CIRC cannot prove automatically. This paper presents an extension of circular coinduction with case analysis constructs and reasoning, as well as its implementation in CIRC. To uniformly prove the soundness of this extension, as well as of past and future extensions of circular coinduction and CIRC, this paper also proposes a general correct-extension technique based on equational interpolants.

Keywords

Case Analysis Special Context Proof System Behavioral Property Reduction Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Eugen-Ioan Goriac
    • 1
  • Dorel Lucanu
    • 1
  • Grigore Roşu
    • 2
  1. 1.Faculty of Computer ScienceAlexandru Ioan Cuza UniversityRomania
  2. 2.Department of Computer ScienceUniversity of IllinoisUrbana-ChampaignUSA

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