Automata Learning for Symbolic Execution

Bernhard Aichernig; Roderick Bloem; Masoud Ebrahimi; Martin Tappler; Johannes Winter

Automata Learning for Symbolic Execution

Bernhard Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Tappler, Johannes Winter

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

Black-box components conceal parts of software execution paths, which makes systematic testing, e. g., via symbolic execution, difficult. In this paper, we use automata learning to facilitate symbolic execution in the presence of black-box components. We substitute black boxes in a software system with learned automata that model them, enabling us to symbolically execute program paths that run through black-boxes. We show that applying the approach on real-world software systems incorporating black-boxes increases code coverage when compared to standard techniques.

Originalsprache	englisch
Titel	2018 Formal Methods in Computer Aided Design, FMCAD 2018, Austin, TX, USA, October 30 - November 2, 2018
Redakteure/-innen	Nikolaj Bjørner, Arie Gurfinkel
Herausgeber (Verlag)	IEEE CS
Seiten	130 - 138
Seitenumfang	9
ISBN (elektronisch)	978-0-9835678-8-2
Publikationsstatus	Veröffentlicht - 2018
Veranstaltung	18th Conference on Formal Methods in Computer-Aided Design - Austin, USA / Vereinigte Staaten Dauer: 30 Okt. 2018 → 2 Nov. 2018 Konferenznummer: 18

Konferenz

Konferenz	18th Conference on Formal Methods in Computer-Aided Design
Kurztitel	FMCAD 2018
Land/Gebiet	USA / Vereinigte Staaten
Ort	Austin
Zeitraum	30/10/18 → 2/11/18

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https://www.cs.utexas.edu/users/hunt/FMCAD/FMCAD18/fmcad2018_proceedings.pdf

Enable-S3 - Europäische Initiative zur Validierung von hochautomatisierten und sicheren Systeme
Bloem, R., Horn, M., Wotawa, F., Bösch, W. & Eichberger, A.
1/05/16 → 30/04/19
Projekt: Forschungsprojekt
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Boano, C. A., Kubin, G., Bloem, R., Horn, M., Pernkopf, F., Zakany, N., Mangard, S., Witrisal, K., Römer, K. U., Aichernig, B., Bösch, W., Baunach, M. C., Tappler, M., Malenko, M., Weiser, S., Eichlseder, M., Leitinger, E., Grosinger, J., Großwindhager, B., Ebrahimi, M., Alothman Alterkawi, A. B., Knoll, C., Teschl, R., Saukh, O., Rath, M., Steinberger, M., Steinbauer-Wagner, G. & Tranninger, M.
1/01/16 → 31/03/22
Projekt: Forschungsprojekt
EU - IMMORTAL - IMMORTAL – Integriertes Modelling, Fault Management, Verifikation und verlässliche Design-Umgebung für Cyber-Physical Systeme.
Bloem, R. & Könighofer, R.
1/03/15 → 28/02/18
Projekt: Forschungsprojekt

Dieses zitieren

Automata Learning for Symbolic Execution. / Aichernig, Bernhard ; Bloem, Roderick; Ebrahimi, Masoud et al.
2018 Formal Methods in Computer Aided Design, FMCAD 2018, Austin, TX, USA, October 30 - November 2, 2018. Hrsg. / Nikolaj Bjørner; Arie Gurfinkel. IEEE CS, 2018. S. 130 - 138.

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Aichernig, B , Bloem, R, Ebrahimi, M, Tappler, M & Winter, J 2018, Automata Learning for Symbolic Execution. in N Bjørner & A Gurfinkel (Hrsg.), 2018 Formal Methods in Computer Aided Design, FMCAD 2018, Austin, TX, USA, October 30 - November 2, 2018. IEEE CS, S. 130 - 138, 18th Conference on Formal Methods in Computer-Aided Design, Austin, Texas, USA / Vereinigte Staaten, 30/10/18. <https://www.cs.utexas.edu/users/hunt/FMCAD/FMCAD18/fmcad2018_proceedings.pdf>

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title = "Automata Learning for Symbolic Execution",

abstract = "Black-box components conceal parts of software execution paths, which makes systematic testing, e. g., via symbolic execution, difficult. In this paper, we use automata learning to facilitate symbolic execution in the presence of black-box components. We substitute black boxes in a software system with learned automata that model them, enabling us to symbolically execute program paths that run through black-boxes. We show that applying the approach on real-world software systems incorporating black-boxes increases code coverage when compared to standard techniques.",

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AB - Black-box components conceal parts of software execution paths, which makes systematic testing, e. g., via symbolic execution, difficult. In this paper, we use automata learning to facilitate symbolic execution in the presence of black-box components. We substitute black boxes in a software system with learned automata that model them, enabling us to symbolically execute program paths that run through black-boxes. We show that applying the approach on real-world software systems incorporating black-boxes increases code coverage when compared to standard techniques.

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BT - 2018 Formal Methods in Computer Aided Design, FMCAD 2018, Austin, TX, USA, October 30 - November 2, 2018

A2 - Bjørner, Nikolaj

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PB - IEEE CS

T2 - 18th Conference on Formal Methods in Computer-Aided Design

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ER -

Automata Learning for Symbolic Execution

Abstract

Konferenz

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Projekte

Enable-S3 - Europäische Initiative zur Validierung von hochautomatisierten und sicheren Systeme

Verlaesslichkeit im Internet der Dinge

EU - IMMORTAL - IMMORTAL – Integriertes Modelling, Fault Management, Verifikation und verlässliche Design-Umgebung für Cyber-Physical Systeme.

Dieses zitieren