Verification, Model Checking, and Abstract Interpretation
Volume 3855 of the series Lecture Notes in Computer Science pp 142-156
Error Control for Probabilistic Model Checking
- Håkan L. S. YounesAffiliated withComputer Science Department, Carnegie Mellon University
Abstract
We introduce a framework for expressing correctness guarantees of model-checking algorithms. The framework allows us to qualitatively compare different solution techniques for probabilistic model checking, both techniques based on statistical sampling and numerical computation of probability estimates. We provide several new insights into the relative merits of the different approaches. In addition, we present a new statistical solution method that can bound the probability of error under any circumstances by sometimes reporting undecided results. Previous statistical solution methods could only bound the probability of error outside of an “indifference region.”
- Title
- Error Control for Probabilistic Model Checking
- Book Title
- Verification, Model Checking, and Abstract Interpretation
- Book Subtitle
- 7th International Conference, VMCAI 2006, Charleston, SC, USA, January 8-10, 2006. Proceedings
- Pages
- pp 142-156
- Copyright
- 2006
- DOI
- 10.1007/11609773_10
- Print ISBN
- 978-3-540-31139-3
- Online ISBN
- 978-3-540-31622-0
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- 3855
- Series ISSN
- 0302-9743
- Publisher
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- Additional Links
- Topics
- Industry Sectors
- eBook Packages
- Editors
-
- E. Allen Emerson (16)
- Kedar S. Namjoshi (17)
- Editor Affiliations
-
- 16. Aiken Computation Laboratory, Harvard University,
- 17. Bell Laboratories, Alcatel-Lucent
- Authors
-
- Håkan L. S. Younes (18)
- Author Affiliations
-
- 18. Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
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