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Combining Black-Box and White-Box Techniques for Learning Register Automata [chapter]

Falk Howar, Bengt Jonsson, Frits Vaandrager
2019 Lecture Notes in Computer Science  
The underlying theoretic framework (active automata learning) was first introduced in a landmark paper by Dana Angluin in 1987 for finite state machines.  ...  In the black-box model of active automata learning this can be costly and require many tests, while in many application scenarios source code is available for analysis.  ...  The Psyco tool integrates active automata learning and dynamic symbolic execution for generating component interfaces [32] .  ... 
doi:10.1007/978-3-319-91908-9_26 fatcat:jqjz3fm5ivbdni62vt2mukjmle

TAGS: A Software Tool for Simulating Transducer Automata

Agustín Esmoris, Carlos Iván Chesñevar, Maráa Paula González
2005 International Journal of Electrical Engineering Education  
This paper introduces TAGS (Transducer Automata Graphical Simulator), a software tool for teaching different aspects of transducer automata theory, a theoretical topic which underlies many aspects of the  ...  TAGS allows to simulate both Moore and Mealy transducer automata, integrating different theoretical concepts associated with them.  ...  In our opinion, the theory and application of transducer automata are very interesting topics for many students.  ... 
doi:10.7227/ijeee.42.4.5 fatcat:k4bcskhcifcafejf5b42s4n6ne

Automated Learning Setups in Automata Learning [chapter]

Maik Merten, Malte Isberner, Falk Howar, Bernhard Steffen, Tiziana Margaria
2012 Lecture Notes in Computer Science  
This paper discusses how test drivers can be created for LearnLib, a flexible automata learning framework.  ...  Test drivers are an essential part of any practical active automata learning setup.  ...  A major obstacle for widespread deployment of active automata learning is the effort needed to design and implement application-fit learning setups.  ... 
doi:10.1007/978-3-642-34026-0_44 fatcat:gmfq65jv2jdrbdgkkllbcbacye

Demonstrating Learning of Register Automata [chapter]

Maik Merten, Falk Howar, Bernhard Steffen, Sofia Cassel, Bengt Jonsson
2012 Lecture Notes in Computer Science  
We will demonstrate the impact of the integration of our most recently developed learning technology for inferring Register Automata into the LearnLib, our framework for active automata learning.  ...  This will not only illustrate the unique power of Register Automata, which allows one to faithfully model data independent systems, but also the ease of enhancing the LearnLib with new functionality.  ...  LearnLib is available for download at http://www.learnlib.de and free for all academic purposes.  ... 
doi:10.1007/978-3-642-28756-5_32 fatcat:rc4kxqzxqvabjg7pgoq4z27xs4

Improving Symbolic Automata Learning with Concolic Execution [chapter]

Donato Clun, Phillip van Heerden, Antonio Filieri, Willem Visser
2020 Lecture Notes in Computer Science  
of symbolic automata, leveraging the additional information that can extracted from concolic execution.  ...  Sound and complete active learning techniques have been developed for several classes of languages and the corresponding automaton representation, however there are outstanding challenges that are limiting  ...  [4] used Angluin-style active learning of symbolic automata for the analysis of finite state string sanitizers and filters.  ... 
doi:10.1007/978-3-030-45234-6_1 fatcat:ax5o2vuwffg3bkeghqiplp2kuu

Aerial Human Activity Recognition Through a Cognitive Architecture and a New Automata Proposal

Milena F. Pinto, Aurelio G. Melo, Andre L. M. Marcato, Camile A. Moraes
2020 Learning and Nonlinear Models  
This research work presents an innovative structure for the well-known Weighted Automata to organize the information from sensors, grouping these measurements into a symbolic representation of actions  ...  An automaton is a specialized structure capable of accepting or rejecting those symbols producing an efficient computation structure for these types of data processing.  ...  Figure 2 : 2 Automata for the Example 1.An important property of this proposal is the execution equivalence with the DFA.  ... 
doi:10.21528/lnlm-vol18-no1-art1 fatcat:ntffyfqw6jfrjoqrmeng65dfdy

Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms [article]

Christian A. Hammerschmidt, Radu State, Sicco Verwer
2017 arXiv   pre-print
We present an interactive version of an evidence-driven state-merging (EDSM) algorithm for learning variants of finite state automata.  ...  Learning these automata often amounts to recovering or reverse engineering the model generating the data despite noisy, incomplete, or imperfectly sampled data sources rather than optimizing a purely numeric  ...  Acknowledgements I would like to thank my collages for the valuable discussions and the feedback.  ... 
arXiv:1707.09430v1 fatcat:rd3vmzlivngf7ixlrngs7zr2qy

Machine Learning for Dynamic Software Analysis: Potentials and Limits (Dagstuhl Seminar 16172)

Amel Bennaceur, Dimitra Giannakopoulou, Reiner Hähnle, Karl Meinke, Marc Herbstritt
2016 Dagstuhl Reports  
The organisers would like to express their gratitude to the participants and the Schloss Dagstuhl team for a productive and exciting seminar. Learning and Testing  ...  values into the symbolic execution process.  ...  Learning algorithms for register automata infer models with parameterized actions, symbolic guards, and memory.  ... 
doi:10.4230/dagrep.6.4.161 dblp:journals/dagstuhl-reports/BennaceurGHM16 fatcat:7t3jl5y7dfanfjeev3k42nmfau

Adaptive Finite State Automata and Genetic Algorithms: Merging Individual Adaptation and Population Evolution [chapter]

H. Pistori, P. S. Martins, A. A. de Castro
2005 Adaptive and Natural Computing Algorithms  
Adaptive finite automata, which are basically finite state automata that can change their internal structures during operation, have proven to be an attractive way to represent simple learning strategies  ...  This paper presents adaptive finite state automata as an alternative formalism to model individuals in a genetic algorithm environment.  ...  Fig. 3 . 3 Adaptive FSA for building Prefix-Tree Acceptor (a) Subjacent Mechanism (b) Adaptive Mechanism secutive symbols.  ... 
doi:10.1007/3-211-27389-1_80 fatcat:jz7jxnf6hjdebcrfhotemquz4y

Towards Model-Based Support For Regression Testing

Anna Gujgiczer, Márton Elekes, Oszkár Semeráth, András Vörös
2017 Zenodo  
In order to ensure correctness, regression testing involves the execution of numerous tests usually written manually by the developers.  ...  Finally, we thank to Zoltán Micskei for his insightful comments.  ...  These symbols are not directly executable inputs for the UUL, but they represent equivalence classes defined by the abstraction rules.  ... 
doi:10.5281/zenodo.291893 fatcat:fcjmtuwlardwhjfvoxn4ptxkgy

Abstracting Symbolic Execution with String Analysis

Daryl Shannon, Sukant Hajra, Alison Lee, Daiqian Zhan, Sarfraz Khurshid
2007 Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007)  
Forward symbolic execution is a technique for program analysis that explores the execution paths of a program by maintaining a symbolic representation of the program state.  ...  By abstracting away the implementation details of strings using finite-state automata, symbolic execution can scale to more complex programs.  ...  Background Forward symbolic execution is a technique for executing a program on symbolic values [16] .  ... 
doi:10.1109/taicpart.2007.4344094 fatcat:mnjfjfzmvvh5tgd6r4dopdwcla

Abstracting Symbolic Execution with String Analysis

Daryl Shannon, Sukant Hajra, Alison Lee, Daiqian Zhan, Sarfraz Khurshid
2007 Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007)  
Forward symbolic execution is a technique for program analysis that explores the execution paths of a program by maintaining a symbolic representation of the program state.  ...  By abstracting away the implementation details of strings using finite-state automata, symbolic execution can scale to more complex programs.  ...  Background Forward symbolic execution is a technique for executing a program on symbolic values [16] .  ... 
doi:10.1109/taic.part.2007.34 fatcat:wwid5s7nxnanbktz6bgjwmrkfi

Fifty years of automata simulation

Pinaki Chakraborty, P. C. Saxena, C. P. Katti
2011 ACM inroads  
The article concludes with an advocacy for continuing research on simulation of automata and integration of automata simulators in teaching.  ...  This article reviews the major initiatives in the field of simulation of automata in the last five decades with emphasis on those automata simulators actually used at universities for teaching.  ...  [60] developed a tool called Thoth for teaching and learning automata theory.  ... 
doi:10.1145/2038876.2038893 fatcat:dyo7kn7lczab3fo54cpcping7q

Towards Automatic Learning of Discrete-Event Models from Simulations

Ashfaq Farooqui, Petter Falkman, Martin Fabian
2018 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)  
We apply the foundational algorithm from the active automata learning community to study the requirements and enhancements needed to be able to derive discrete event models from virtual simulations.  ...  While model-based approaches allow for offline verification and validation before physical commissioning, and have other advantages over existing methods, they do have their own challenges.  ...  For example, for two sets A = {a} and B = {b}, set concatenation is represented by A · B and symbol concatenation by ab. Note that A · B = {ab}.  ... 
doi:10.1109/coase.2018.8560451 dblp:conf/case/FarooquiFF18 fatcat:l4wftnmwnbbkhpzwxtrmbntvxy

Using theoretical computer simulators for formal languages and automata theory

Carlos I. Chesñevar, María L. Cobo, William Yurcik
2003 ACM SIGCSE Bulletin  
Both formal languages and automata theory (FLAT) are core to the CS curricula but are difficult to teach and to learn.  ...  We conclude with general recommendations for integrating FLAT software tools into an established curriculum.  ...  Acknowledgments The authors want to thank Professor Jürgen Dix (University of Manchester, UK) for his comments on the use of busy beaver functions as additional motivation when teaching Turing machines  ... 
doi:10.1145/782941.782975 fatcat:jgl47n7ykrbkdcescfu2fybv2e
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