Learning regular sets from queries and counterexamples
Information and Computation
Inference of finite automata using homing sequences
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Model checking
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Model Generation by Moderated Regular Extrapolation
FASE '02 Proceedings of the 5th International Conference on Fundamental Approaches to Software Engineering
Counterexample-guided abstraction refinement for symbolic model checking
Journal of the ACM (JACM)
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HLDVT '04 Proceedings of the High-Level Design Validation and Test Workshop, 2004. Ninth IEEE International
Learning Parameterized State Machine Model for Integration Testing
COMPSAC '07 Proceedings of the 31st Annual International Computer Software and Applications Conference - Volume 02
Hybrid test of web applications with webtest
TAV-WEB '08 Proceedings of the 2008 workshop on Testing, analysis, and verification of web services and applications
Automated Assume-Guarantee Reasoning by Abstraction Refinement
CAV '08 Proceedings of the 20th international conference on Computer Aided Verification
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International Journal on Software Tools for Technology Transfer (STTT) - Special Section on FMICS 05
FM '09 Proceedings of the 2nd World Congress on Formal Methods
Learning assumptions for compositional verification
TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
Regular inference for state machines using domains with equality tests
FASE'08/ETAPS'08 Proceedings of the Theory and practice of software, 11th international conference on Fundamental approaches to software engineering
Inference and abstraction of the biometric passport
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
From ZULU to RERS: lessons learned in the ZULU challenge
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
Inference of event-recording automata using timed decision trees
CONCUR'06 Proceedings of the 17th international conference on Concurrency Theory
Regular inference for state machines with parameters
FASE'06 Proceedings of the 9th international conference on Fundamental Approaches to Software Engineering
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
Inferring canonical register automata
VMCAI'12 Proceedings of the 13th international conference on Verification, Model Checking, and Abstract Interpretation
Learning boolean functions incrementally
CAV'12 Proceedings of the 24th international conference on Computer Aided Verification
A theory of history dependent abstractions for learning interface automata
CONCUR'12 Proceedings of the 23rd international conference on Concurrency Theory
LearnLib tutorial: from finite automata to register interface programs
ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: technologies for mastering change - Volume Part I
Symbolic learning of component interfaces
SAS'12 Proceedings of the 19th international conference on Static Analysis
Satisfying requirements for pervasive service compositions
Proceedings of the 7th Workshop on Models@run.time
Hybrid learning: interface generation through static, dynamic, and symbolic analysis
Proceedings of the 2013 International Symposium on Software Testing and Analysis
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Abstraction is the key when learning behavioral models of realistic systems, but also the cause of a major problem: the introduction of non-determinism. In this paper, we introduce a method for refining a given abstraction to automatically regain a deterministic behavior on-the-fly during the learning process. Thus the control over abstraction becomes part of the learning process, with the effect that detected nondeterminism does not lead to failure, but to a dynamic alphabet abstraction refinement. Like automata learning itself, this method in general is neither sound nor complete, but it also enjoys similar convergence properties even for infinite systems as long as the concrete system itself behaves deterministically, as illustrated along a concrete example.