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Dealing with uncertainty in verification of nondeterministic systems

Published: 11 November 2014 Publication History

Abstract

Uncertainty complicates the formal verification of nondeterministic systems. Unpredictable changes and alterations in their environments can lead an invalid verification results and the decrease of confidence degree of these systems. However, current literature provides little account of addressing the uncertainty in formal verification. To address this problem, the goal of this research is to provide a method based on perturbation analysis for probabilistic model checking of nondeterministic systems which are modelled as Markov Decision Processes. And to apply our expected contributions to ubiquitous systems due to inherent presence of environment uncertainty and their resource limitations.

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Cited By

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  • (2019)When and Why Do Software Developers Face Uncertainty?2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS)10.1109/QRS.2019.00045(288-299)Online publication date: Jul-2019
  • (2019)Modular Programming and Reasoning for Living with UncertaintySoftware Technologies10.1007/978-3-030-29157-0_10(220-244)Online publication date: 13-Aug-2019
  • (2017)iArch-UProceedings of the 9th International Workshop on Modelling in Software Engineering10.5555/3104068.3104080(40-46)Online publication date: 20-May-2017
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cover image ACM Conferences
FSE 2014: Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering
November 2014
856 pages
ISBN:9781450330565
DOI:10.1145/2635868
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 11 November 2014

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Author Tags

  1. Markov Decision Processes
  2. Perturbation Analysis
  3. Probabilistic Model Checking
  4. Uncertainty

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Overall Acceptance Rate 17 of 128 submissions, 13%

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Cited By

View all
  • (2019)When and Why Do Software Developers Face Uncertainty?2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS)10.1109/QRS.2019.00045(288-299)Online publication date: Jul-2019
  • (2019)Modular Programming and Reasoning for Living with UncertaintySoftware Technologies10.1007/978-3-030-29157-0_10(220-244)Online publication date: 13-Aug-2019
  • (2017)iArch-UProceedings of the 9th International Workshop on Modelling in Software Engineering10.5555/3104068.3104080(40-46)Online publication date: 20-May-2017
  • (2017)iArch-U: Interface-Centric Integrated Uncertainty-Aware Development Environment2017 IEEE/ACM 9th International Workshop on Modelling in Software Engineering (MiSE)10.1109/MiSE.2017.7(40-46)Online publication date: May-2017
  • (2015)Modularity for uncertaintyProceedings of the Seventh International Workshop on Modeling in Software Engineering10.5555/2820489.2820492(7-12)Online publication date: 16-May-2015
  • (2015)Modularity for UncertaintyProceedings of the 2015 IEEE/ACM 7th International Workshop on Modeling in Software Engineering10.1109/MiSE.2015.9(7-12)Online publication date: 16-May-2015

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