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Information and Computation
Deciding bisimulation equivalences for a class of non-finite-state programs
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Inference of finite automata using homing sequences
Information and Computation
An introduction to computational learning theory
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The SLAM project: debugging system software via static analysis
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
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Expressing interesting properties of programs in propositional temporal logic
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Switching and Finite Automata Theory: Computer Science Series
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FASE '02 Proceedings of the 5th International Conference on Fundamental Approaches to Software Engineering
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FORTE XII / PSTV XIX '99 Proceedings of the IFIP TC6 WG6.1 Joint International Conference on Formal Description Techniques for Distributed Systems and Communication Protocols (FORTE XII) and Protocol Specification, Testing and Verification (PSTV XIX)
TACAS '02 Proceedings of the 8th International Conference on Tools and Algorithms for the Construction and Analysis of Systems
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TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
Integration testing of distributed components based on learning parameterized i/o models
FORTE'06 Proceedings of the 26th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems
Regular inference for state machines with parameters
FASE'06 Proceedings of the 9th international conference on Fundamental Approaches to Software Engineering
Learning and integration of parameterized components through testing
TestCom'07/FATES'07 Proceedings of the 19th IFIP TC6/WG6.1 international conference, and 7th international conference on Testing of Software and Communicating Systems
Automatic synthesis of behavior protocols for composable web-services
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Proceedings of the 2010 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems
Learning of event-recording automata
Theoretical Computer Science
Generating models of infinite-state communication protocols using regular inference with abstraction
ICTSS'10 Proceedings of the 22nd IFIP WG 6.1 international conference on Testing software and systems
Inferring compact models of communication protocol entities
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
On handling data in automata learning: considerations from the CONNECT perspective
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part II
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VMCAI'11 Proceedings of the 12th international conference on Verification, model checking, and abstract interpretation
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ATVA'11 Proceedings of the 9th international conference on Automated technology for verification and analysis
Inferring canonical register automata
VMCAI'12 Proceedings of the 13th international conference on Verification, Model Checking, and Abstract Interpretation
Enemy of the state: a state-aware black-box web vulnerability scanner
Security'12 Proceedings of the 21st USENIX conference on Security symposium
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ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: technologies for mastering change - Volume Part I
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Sigma*: symbolic learning of input-output specifications
POPL '13 Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Producing software by integration: challenges and research directions (keynote)
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
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Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to a selected sequence of input strings. We generalize regular inference techniques to infer a class of state machines with an infinite state space. We consider Mealy machines extended with state variables that can assume values from a potentially unbounded domain. These values can be passed as parameters in input and output symbols, and can be used in tests for equality between state variables and/or message parameters. This is to our knowledge the first extension of regular inference to infinite-state systems. We intend to use these techniques to generate models of communication protocols from observations of their input-output behavior. Such protocols often have parameters that represent node adresses, connection identifiers, etc. that have a large domain, and on which test for equality is the only meaningful operation. Our extension consists of two phases. In the first phase we apply an existing inference technique for finite-state Mealy machines to generate a model for the case that the values are taken from a small data domain. In the second phase we transform this finite-state Mealy machine into an infinite-state Mealy machine by folding it into a compact symbolic form.