research-article

Leveraging Weighted Automata in Compositional Reasoning about Concurrent Probabilistic Systems

Authors:

Lijun ZhangAuthors Info & Claims

ACM SIGPLAN Notices, Volume 50, Issue 1

Pages 503 - 514

https://doi.org/10.1145/2775051.2676998

Published: 14 January 2015 Publication History

Abstract

We propose the first sound and complete learning-based compositional verification technique for probabilistic safety properties on concurrent systems where each component is an Markov decision process. Different from previous works, weighted assumptions are introduced to attain completeness of our framework. Since weighted assumptions can be implicitly represented by multi-terminal binary decision diagrams (MTBDD's), we give an L*-based learning algorithm for MTBDD's to infer weighted assumptions. Experimental results suggest promising outlooks for our compositional technique.

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Cited By

Li YChen YZhang LLiu D(2017)A Novel Learning Algorithm for Büchi Automata Based on Family of DFAs and Classification TreesTools and Algorithms for the Construction and Analysis of Systems10.1007/978-3-662-54577-5_12(208-226)Online publication date: 31-Mar-2017
https://doi.org/10.1007/978-3-662-54577-5_12
He FMao SWang B(2016)Learning-Based Assume-Guarantee Regression VerificationComputer Aided Verification10.1007/978-3-319-41528-4_17(310-328)Online publication date: 13-Jul-2016
https://doi.org/10.1007/978-3-319-41528-4_17
Eisentraut CGodskesen JHermanns HSong LZhang L(2015)Probabilistic Bisimulation for Realistic SchedulersFM 2015: Formal Methods10.1007/978-3-319-19249-9_16(248-264)Online publication date: 2015
https://doi.org/10.1007/978-3-319-19249-9_16
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Index Terms

Leveraging Weighted Automata in Compositional Reasoning about Concurrent Probabilistic Systems
1. Software and its engineering
  1. Software organization and properties
    1. Software functional properties
      1. Formal methods
        Model checking
2. Theory of computation
  1. Logic
    1. Verification by model checking

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Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 50, Issue 1

POPL '15

January 2015

682 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/2775051

Editor:
Andy Gill
University of Kansas, Lawrence, KS

Issue’s Table of Contents

POPL '15: Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages
January 2015
716 pages
ISBN:9781450333009
DOI:10.1145/2676726
General Chair:
Sriram Rajamani
Microsoft Research, India
,
Program Chair:
David Walker
Princeton University, USA

Copyright © 2015 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 January 2015

Published in SIGPLAN Volume 50, Issue 1

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Cited By

Li YChen YZhang LLiu D(2017)A Novel Learning Algorithm for Büchi Automata Based on Family of DFAs and Classification TreesTools and Algorithms for the Construction and Analysis of Systems10.1007/978-3-662-54577-5_12(208-226)Online publication date: 31-Mar-2017
https://doi.org/10.1007/978-3-662-54577-5_12
He FMao SWang B(2016)Learning-Based Assume-Guarantee Regression VerificationComputer Aided Verification10.1007/978-3-319-41528-4_17(310-328)Online publication date: 13-Jul-2016
https://doi.org/10.1007/978-3-319-41528-4_17
Eisentraut CGodskesen JHermanns HSong LZhang L(2015)Probabilistic Bisimulation for Realistic SchedulersFM 2015: Formal Methods10.1007/978-3-319-19249-9_16(248-264)Online publication date: 2015
https://doi.org/10.1007/978-3-319-19249-9_16
Li YChen YZhang LLiu D(2021)A novel learning algorithm for Büchi automata based on family of DFAs and classification treesInformation and Computation10.1016/j.ic.2020.104678281:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.ic.2020.104678
Zhang LYang PSong LHermanns HEisentraut CJansen DGodskesen J(2018)Probabilistic bisimulation for realistic schedulersActa Informatica10.1007/s00236-018-0313-155:6(461-488)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s00236-018-0313-1
Li YTurrini AZhang LSchewe S(2017)Learning to Complement Büchi AutomataVerification, Model Checking, and Abstract Interpretation10.1007/978-3-319-73721-8_15(313-335)Online publication date: 29-Dec-2017
https://doi.org/10.1007/978-3-319-73721-8_15
He FGao XWang MWang BZhang L(2016)Learning Weighted Assumptions for Compositional Verification of Markov Decision ProcessesACM Transactions on Software Engineering and Methodology10.1145/290794325:3(1-39)Online publication date: 6-Jun-2016
https://dl.acm.org/doi/10.1145/2907943

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