Reverse Engineering Through Automata Learning

Doron Peled

doi:10.1007/978-3-030-87348-6_11

Reverse Engineering Through Automata Learning

Doron Peled

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

We suggest a method for constructing a system that needs to satisfy some given formal specification φ. In our setting, a black box system satisfying φ is given; we can only interface with the system through experiments and cannot duplicate it or modify its design. Instead of developing a system satisfying φ from scratch, either manually or through algorithmic synthesis, we use a reverse engineering method based on a combination of Angluin’s automata learning algorithm and model checking.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	182-192
Number of pages	11
DOIs	https://doi.org/10.1007/978-3-030-87348-6_11
State	Published - 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13065 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Funding

The research was partially funded by Israeli Science Foundation grant 1464/18: “Efficient Runtime Verification for Systems with Lots of Data and its Applications.”

Funders	Funder number
Israel Science Foundation	1464/18

Access to Document

10.1007/978-3-030-87348-6_11

Cite this

Peled, D. (2021). Reverse Engineering Through Automata Learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 182-192). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13065 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-87348-6_11

Peled, Doron. / Reverse Engineering Through Automata Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH, 2021. pp. 182-192 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Peled, D 2021, Reverse Engineering Through Automata Learning. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13065 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 182-192. https://doi.org/10.1007/978-3-030-87348-6_11

Reverse Engineering Through Automata Learning. / Peled, Doron.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH, 2021. p. 182-192 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13065 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Peled D. Reverse Engineering Through Automata Learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH. 2021. p. 182-192. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-87348-6_11

Reverse Engineering Through Automata Learning

Abstract

Publication series

Bibliographical note

Funding

Access to Document

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