Adaptive Learning for Learn-Based Regression Testing

David Huistra; Jeroen Meijer; Jaco van de Pol

doi:10.1007/978-3-030-00244-2_11

Adaptive Learning for Learn-Based Regression Testing

David Huistra, Jeroen Meijer, Jaco van de Pol

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

11 Citations (Scopus)

249 Downloads (Pure)

Abstract

Regression testing is an important activity to prevent the introduction of regressions into software updates. Learn-based testing can be used to automatically check new versions of a system for regressions on a system level. This is done by learning a model of the system and model checking this model for system property violations.

Learning the model of a large system can take an unpractical amount of time however. In this work we investigate if the concept of adaptive learning can improve the learning speed of a model in a regression testing scenario.

We have performed several experiments with this technique on two systems: ToDoMVC and SSH. We find that there can be a large benefit to using adaptive learning. In addition we find three main factors that influence the benefit of adaptive learning. There are however also some shortcomings to adaptive learning that should be investigated further.

Original language	English
Title of host publication	Formal Methods for Industrial Critical Systems
Subtitle of host publication	23rd International Conference, FMICS 2018, Maynooth, Ireland, September 3-4, 2018, Proceedings
Editors	Falk Howar, Jiri Barnat
Publisher	Springer
Pages	162-177
Number of pages	16
ISBN (Electronic)	978-3-030-00244-2
ISBN (Print)	978-3-030-00243-5
DOIs	https://doi.org/10.1007/978-3-030-00244-2_11
Publication status	Published - Sept 2018
Event	23rd International Conference on Formal Methods for Industrial Critical Systems, FMICS 2018 - Maynooth University, Maynooth, Ireland Duration: 3 Sept 2018 → 4 Sept 2018 Conference number: 23 http://fmics2018.fi.muni.cz/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	11119

Conference

Conference	23rd International Conference on Formal Methods for Industrial Critical Systems, FMICS 2018
Abbreviated title	FMICS 2018
Country/Territory	Ireland
City	Maynooth
Period	3/09/18 → 4/09/18
Internet address	http://fmics2018.fi.muni.cz/

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10.1007/978-3-030-00244-2_11

ArticleAccepted author version, 228 KB

Cite this

Huistra, D., Meijer, J., & Pol, J. V. D. (2018). Adaptive Learning for Learn-Based Regression Testing. In F. Howar, & J. Barnat (Eds.), Formal Methods for Industrial Critical Systems: 23rd International Conference, FMICS 2018, Maynooth, Ireland, September 3-4, 2018, Proceedings (pp. 162-177). (Lecture Notes in Computer Science; Vol. 11119). Springer. https://doi.org/10.1007/978-3-030-00244-2_11

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title = "Adaptive Learning for Learn-Based Regression Testing",

abstract = "Regression testing is an important activity to prevent the introduction of regressions into software updates. Learn-based testing can be used to automatically check new versions of a system for regressions on a system level. This is done by learning a model of the system and model checking this model for system property violations.Learning the model of a large system can take an unpractical amount of time however. In this work we investigate if the concept of adaptive learning can improve the learning speed of a model in a regression testing scenario.We have performed several experiments with this technique on two systems: ToDoMVC and SSH. We find that there can be a large benefit to using adaptive learning. In addition we find three main factors that influence the benefit of adaptive learning. There are however also some shortcomings to adaptive learning that should be investigated further.",

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booktitle = "Formal Methods for Industrial Critical Systems",

address = "Germany",

note = "23rd International Conference on Formal Methods for Industrial Critical Systems, FMICS 2018, FMICS 2018 ; Conference date: 03-09-2018 Through 04-09-2018",

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Huistra, D, Meijer, J & Pol, JVD 2018, Adaptive Learning for Learn-Based Regression Testing. in F Howar & J Barnat (eds), Formal Methods for Industrial Critical Systems: 23rd International Conference, FMICS 2018, Maynooth, Ireland, September 3-4, 2018, Proceedings. Lecture Notes in Computer Science, vol. 11119, Springer, pp. 162-177, 23rd International Conference on Formal Methods for Industrial Critical Systems, FMICS 2018, Maynooth, Ireland, 3/09/18. https://doi.org/10.1007/978-3-030-00244-2_11

Adaptive Learning for Learn-Based Regression Testing. / Huistra, David; Meijer, Jeroen; Pol, Jaco van de.
Formal Methods for Industrial Critical Systems: 23rd International Conference, FMICS 2018, Maynooth, Ireland, September 3-4, 2018, Proceedings. ed. / Falk Howar; Jiri Barnat. Springer, 2018. p. 162-177 (Lecture Notes in Computer Science; Vol. 11119).

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

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Huistra D, Meijer J, Pol JVD. Adaptive Learning for Learn-Based Regression Testing. In Howar F, Barnat J, editors, Formal Methods for Industrial Critical Systems: 23rd International Conference, FMICS 2018, Maynooth, Ireland, September 3-4, 2018, Proceedings. Springer. 2018. p. 162-177. (Lecture Notes in Computer Science). Epub 2018 Aug 30. doi: 10.1007/978-3-030-00244-2_11

Adaptive Learning for Learn-Based Regression Testing

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