Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Incremental Learning based Testing for Reactive Systems
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-9706-5008
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
2011 (English)In: / [ed] Martin Gogolla and Burkhart Wolff, 2011, 134-151 p.Conference paper, Published paper (Refereed)
Abstract [en]

We show how the paradigm of learning-based testing (LBT)can be applied to automate specification-based black-box testing of reactivesystems. Since reactive systems can be modeled as Kripke structures,we introduce an efficient incremental learning algorithm IKL forsuch structures. We show how an implementation of this algorithm combinedwith an efficient model checker such as NuSMV yields an effectivelearning-based testing architecture for automated test case generation(ATCG), execution and evaluation, starting from temporal logic requirements.

Place, publisher, year, edition, pages
2011. 134-151 p.
Series
Lecture Notes In Computer Science, 6706
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-37339DOI: 10.1007/978-3-642-21768-5_11Scopus ID: 2-s2.0-79960247126ISBN: 978-3-642-21767-8 (print)OAI: oai:DiVA.org:kth-37339DiVA: diva2:433301
Conference
5th International Conference on Tests and Proofs (TAP)
Note
QC 20110822Available from: 2011-08-09 Created: 2011-08-09 Last updated: 2013-03-12Bibliographically approved
In thesis
1. Incremental Learning and Testing of Reactive Systems
Open this publication in new window or tab >>Incremental Learning and Testing of Reactive Systems
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis concerns the design, implementation and evaluation of a specification based testing architecture for reactive systems using the paradigm of learning-based testing. As part of this work we have designed, verified and implemented new incremental learning algorithms for DFA and Kripke structures.These have been integrated with the NuSMV model checker to give a new learning-based testing architecture. We have evaluated our architecture on case studies and shown that the method is effective.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. x, 45 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2011:14
Keyword
Incremental learning, software testing, specification based testing, reactive systems, model checking
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-37763 (URN)978-91-7501-062-5 (ISBN)
Presentation
2011-09-30, K2, Teknikringen 28, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
QC 20110822Available from: 2011-08-22 Created: 2011-08-17 Last updated: 2011-08-22Bibliographically approved
2. Algorithms and Tools for Learning-based Testing of Reactive Systems
Open this publication in new window or tab >>Algorithms and Tools for Learning-based Testing of Reactive Systems
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis we investigate the feasibility of learning-based testing (LBT) as a viable testing methodology for reactive systems. In LBT, a large number of test cases are automatically generated from black-box requirements for the system under test (SUT) by combining an incremental learning algorithm with a model checking algorithm. The integration of the SUT with these algorithms in a feedback loop optimizes test generation using the results from previous outcomes. The verdict for each test case is also created automatically in LBT.

To realize LBT practically, existing algorithms in the literature both for complete and incremental learning of finite automata were studied. However, limitations in these algorithms led us to design, verify and implement new incremental learning algorithms for DFA and Kripke structures. On the basis of these algorithms we implemented an LBT architecture in a practical tool called LBTest which was evaluated on pedagogical and industrial case studies.

The results obtained from both types of case studies show that LBT is an effective methodology which discovers errors in reactive SUTs quickly and can be scaled to test industrial applications. We believe that this technology is easily transferrable to industrial users because of its high degree of automation.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. xii, 79 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2013:03
Keyword
specification-based testing, learning-based testing, reactive systems, LBTest, case studies
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-119267 (URN)978-91-7501-674-0 (ISBN)
Public defence
2013-04-16, F3, Lindstedtsvägen 26, Kungliga Tekniska Högskolan, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20130312

Available from: 2013-03-12 Created: 2013-03-11 Last updated: 2013-03-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Authority records BETA

Meinke, Karl

Search in DiVA

By author/editor
Meinke, KarlSindhu, Muddassar
By organisation
Theoretical Computer Science, TCS
Computer Science

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 257 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf