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ProbVerus: Probabilistic Symbolic Model Checking

  • Vicky Hartonas-Garmhausen
  • Sergio Campos
  • Ed Clarke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1601)

Abstract

Model checking can tell us whether a system is correct; probabilistic model checking can also tell us whether a system is timely and reliable. Moreover, probabilistic model checking allows one to verify properties that may not be true with probability one, but may still hold with an acceptable probability. The challenge in developing a probabilistic model checker able to handle realistic systems is the construction of the state space and the necessity to solve huge systems of linear equations. To address this problem, we have developed ProbVerus, a tool for the formal verification of probabilistic real-time systems. ProbVerus is an implementation of probabilistic computation tree logic (PCTL) model checking using symbolic techniques. We present ProbVerus, demonstrate its use with a simple manufacturing example, and report the current status of the tool. With ProbVerus, we have been able to analyze, within minutes, the safety logic of a railway interlocking controller with 1027 states.

Keywords

Model Check Transition Probability Matrix Formal Verification Atomic Proposition Binary Decision Diagram 
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 1999

Authors and Affiliations

  • Vicky Hartonas-Garmhausen
    • 1
  • Sergio Campos
    • 2
  • Ed Clarke
    • 3
  1. 1.Department of Engineering and Public PolicyCarnegie Mellon UniversityPittsburghUSA
  2. 2.Federal University of MinasGeraisBrasil
  3. 3.Department of Computer ScienceCarnegie Mellon UniversityPittsburghUSA

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