Learning regular sets from queries and counterexamples
Information and Computation
Tentative steps toward a development method for interfering programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Modeling and verification of randomized distributed real-time systems
Modeling and verification of randomized distributed real-time systems
Probabilistic simulations for probabilistic processes
Nordic Journal of Computing
Compositional Methods for Probabilistic Systems
CONCUR '01 Proceedings of the 12th International Conference on Concurrency Theory
A Compositional Trace-Based Semantics for Probabilistic Automata
CONCUR '95 Proceedings of the 6th International Conference on Concurrency Theory
Model Checking of Probabalistic and Nondeterministic Systems
Proceedings of the 15th Conference on Foundations of Software Technology and Theoretical Computer Science
Component Verification with Automatically Generated Assumptions
Automated Software Engineering
LiQuor: A tool for Qualitative and Quantitative Linear Time analysis of Reactive Systems
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
Observing Branching Structure through Probabilistic Contexts
SIAM Journal on Computing
Automated assumption generation for compositional verification
Formal Methods in System Design
Learning to divide and conquer: applying the L* algorithm to automate assume-guarantee reasoning
Formal Methods in System Design
Automatic symbolic compositional verification by learning assumptions
Formal Methods in System Design
ProbDiVinE-MC: Multi-core LTL Model Checker for Probabilistic Systems
QEST '08 Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems
Counterexample Generation in Probabilistic Model Checking
IEEE Transactions on Software Engineering
Learning Minimal Separating DFA's for Compositional Verification
TACAS '09 Proceedings of the 15th International Conference on Tools and Algorithms for the Construction and Analysis of Systems: Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2009,
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Optimized L*-based assume-guarantee reasoning
TACAS'07 Proceedings of the 13th international conference on Tools and algorithms for the construction and analysis of systems
Learning assumptions for compositional verification
TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
Extending automated compositional verification to the full class of omega-regular languages
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Probabilistic Contracts: A Compositional Reasoning Methodology for the Design of Stochastic Systems
ACSD '10 Proceedings of the 2010 10th International Conference on Application of Concurrency to System Design
Compositional Verification of Probabilistic Systems Using Learning
QEST '10 Proceedings of the 2010 Seventh International Conference on the Quantitative Evaluation of Systems
Quantitative multi-objective verification for probabilistic systems
TACAS'11/ETAPS'11 Proceedings of the 17th international conference on Tools and algorithms for the construction and analysis of systems: part of the joint European conferences on theory and practice of software
Switched probabilistic i/o automata
ICTAC'04 Proceedings of the First international conference on Theoretical Aspects of Computing
libalf: the automata learning framework
CAV'10 Proceedings of the 22nd international conference on Computer Aided Verification
Automated assume-guarantee reasoning through implicit learning
CAV'10 Proceedings of the 22nd international conference on Computer Aided Verification
Assume-Guarantee verification for probabilistic systems
TACAS'10 Proceedings of the 16th international conference on Tools and Algorithms for the Construction and Analysis of Systems
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
SPIN'06 Proceedings of the 13th international conference on Model Checking Software
ProbPoly: a probabilistic inductive logic programming framework with application in model checking
Proceedings of the International Workshop on Machine Learning Technologies in Software Engineering
Learning Probabilistic Systems from Tree Samples
LICS '12 Proceedings of the 2012 27th Annual IEEE/ACM Symposium on Logic in Computer Science
Assume-guarantee abstraction refinement for probabilistic systems
CAV'12 Proceedings of the 24th international conference on Computer Aided Verification
Compositional reverification of probabilistic safety properties for large-scale complex IT systems
Proceedings of the 17th Monterey conference on Large-Scale Complex IT Systems: development, operation and management
From software verification to `everyware' verification
Computer Science - Research and Development
Compositional probabilistic verification through multi-objective model checking
Information and Computation
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Probabilistic verification techniques have been applied to the formal modelling and analysis of a wide range of systems, from communication protocols such as Bluetooth, to nanoscale computing devices, to biological cellular processes. In order to tackle the inherent challenge of scalability, compositional approaches to verification are sorely needed. An example is assume-guarantee reasoning, where each component of a system is analysed independently, using assumptions about the other components that it interacts with. We discuss recent developments in the area of automated compositional verification techniques for probabilistic systems. In particular, we describe techniques to automatically generate probabilistic assumptions that can be used as the basis for compositional reasoning. We do so using algorithmic learning techniques, which have already proved to be successful for the generation of assumptions for compositional verification of non-probabilistic systems. We also present recent improvements and extensions to this work and survey some of the promising potential directions for further research in this area.