Pitfalls in applying model learning to industrial legacy software

Omar al Duhaiby; Arjan Mooij; Hans van Wezep; Jan Friso Groote

doi:10.1007/978-3-030-03427-6_13

Pitfalls in applying model learning to industrial legacy software

Omar al Duhaiby, Arjan Mooij, Hans van Wezep, Jan Friso Groote

Formal System Analysis

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

5 Citations (Scopus)

2 Downloads (Pure)

Abstract

Maintaining legacy software is one of the most common struggles of the software industry, being costly yet essential. We tackle that problem by providing better understanding of software by extracting behavioural models using the model learning technique. The used technique interacts with a running component and extracts abstract models that would help developers make better informed decisions. As promising in theory, as slippery in application it is, however. This report describes our experience in applying model learning to legacy software, and aims to prepare the newcomer for what shady pitfalls lie therein as well as provide the seasoned researcher with concrete cases and open problems. We narrate our experience in analysing certain legacy components at Philips Healthcare describing challenges faced, solutions implemented, and lessons learned.

Original language	English
Title of host publication	Leveraging Applications of Formal Methods, Verification and Validation. Industrial Practice - 8th International Symposium, ISoLA 2018, Proceedings
Editors	Tiziana Margaria, Bernhard Steffen
Place of Publication	Cham
Publisher	Springer
Pages	121-138
Number of pages	18
ISBN (Electronic)	978-3-030-03427-6
ISBN (Print)	978-3-030-03426-9
DOIs	https://doi.org/10.1007/978-3-030-03427-6_13
Publication status	Published - 30 Oct 2018
Event	8th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, (ISoLA 2018) - Limassol, Cyprus Duration: 5 Nov 2018 → 9 Nov 2018 http://www.isola-conference.org/isola2018/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11247 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, (ISoLA 2018)
Abbreviated title	ISoLA2018
Country/Territory	Cyprus
City	Limassol
Period	5/11/18 → 9/11/18
Internet address	http://www.isola-conference.org/isola2018/

Keywords

Active learning
Legacy software
Model learning

Access to Document

10.1007/978-3-030-03427-6_13

Cite this

al Duhaiby, O., Mooij, A., van Wezep, H., & Groote, J. F. (2018). Pitfalls in applying model learning to industrial legacy software. In T. Margaria, & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verification and Validation. Industrial Practice - 8th International Symposium, ISoLA 2018, Proceedings (pp. 121-138). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11247 LNCS). Springer. https://doi.org/10.1007/978-3-030-03427-6_13

al Duhaiby, Omar ; Mooij, Arjan ; van Wezep, Hans et al. / Pitfalls in applying model learning to industrial legacy software. Leveraging Applications of Formal Methods, Verification and Validation. Industrial Practice - 8th International Symposium, ISoLA 2018, Proceedings. editor / Tiziana Margaria ; Bernhard Steffen. Cham : Springer, 2018. pp. 121-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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al Duhaiby, O, Mooij, A, van Wezep, H & Groote, JF 2018, Pitfalls in applying model learning to industrial legacy software. in T Margaria & B Steffen (eds), Leveraging Applications of Formal Methods, Verification and Validation. Industrial Practice - 8th International Symposium, ISoLA 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11247 LNCS, Springer, Cham, pp. 121-138, 8th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, (ISoLA 2018), Limassol, Cyprus, 5/11/18. https://doi.org/10.1007/978-3-030-03427-6_13

Pitfalls in applying model learning to industrial legacy software. / al Duhaiby, Omar; Mooij, Arjan; van Wezep, Hans et al.

Leveraging Applications of Formal Methods, Verification and Validation. Industrial Practice - 8th International Symposium, ISoLA 2018, Proceedings. ed. / Tiziana Margaria; Bernhard Steffen. Cham : Springer, 2018. p. 121-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11247 LNCS).

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

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AB - Maintaining legacy software is one of the most common struggles of the software industry, being costly yet essential. We tackle that problem by providing better understanding of software by extracting behavioural models using the model learning technique. The used technique interacts with a running component and extracts abstract models that would help developers make better informed decisions. As promising in theory, as slippery in application it is, however. This report describes our experience in applying model learning to legacy software, and aims to prepare the newcomer for what shady pitfalls lie therein as well as provide the seasoned researcher with concrete cases and open problems. We narrate our experience in analysing certain legacy components at Philips Healthcare describing challenges faced, solutions implemented, and lessons learned.

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al Duhaiby O, Mooij A, van Wezep H, Groote JF. Pitfalls in applying model learning to industrial legacy software. In Margaria T, Steffen B, editors, Leveraging Applications of Formal Methods, Verification and Validation. Industrial Practice - 8th International Symposium, ISoLA 2018, Proceedings. Cham: Springer. 2018. p. 121-138. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-03427-6_13

Pitfalls in applying model learning to industrial legacy software

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Keywords

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