Software process analysis methodology-a methodology based on lessons learned in embracing legacy software

Maikel Leemans; Wil M.P. van der Aalst; Mark G.J. van den Brand; Ramon R.H. Schiffelers; Leonard Lensink

doi:10.1109/ICSME.2018.00076

Software process analysis methodology-a methodology based on lessons learned in embracing legacy software

Maikel Leemans
, Wil M.P. van der Aalst
, Mark G.J. van den Brand
, Ramon R.H. Schiffelers
, Leonard Lensink

Software Engineering and Technology

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

7 Citaten (Scopus)

2 Downloads (Pure)

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Over the last decades, the complexity of high-Tech systems, and the software systems controlling them, has increased considerably. In practice, it is hard to keep knowledge and documentation of these ever-evolving software systems up-To-date with their actual realization; we are dealing with legacy software. Clearly, this lack of knowledge, insight, and understanding is more and more becoming a critical issue. Process mining provides an interesting opportunity to improve understanding and analyze software behavior based on observations from the system on the run. However, a concrete software process analysis methodology was lacking. This paper 1) discusses a software process analysis case study at ASML, a large high-Tech company, and, based on the lessons learned, 2) presents a concrete methodology for analyzing software processes. The presented methodology actively includes the system under analysis and is based on practical experiences in applying process mining on industrial-scale legacy software.

Originele taal-2	Engels
Titel	Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018
Plaats van productie	Piscataway
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	665-674
Aantal pagina's	10
ISBN van elektronische versie	978-1-5386-7870-1
ISBN van geprinte versie	978-1-5386-7871-8
DOI's	https://doi.org/10.1109/ICSME.2018.00076
Status	Gepubliceerd - 9 nov. 2018
Evenement	34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018) - Madrid, Spanje Duur: 23 sep. 2018 → 29 sep. 2018 Congresnummer: 34

Congres

Congres	34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018)
Verkorte titel	ICSME
Land/Regio	Spanje
Stad	Madrid
Periode	23/09/18 → 29/09/18

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10.1109/ICSME.2018.00076

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Leemans, M., van der Aalst, W. M. P., van den Brand, M. G. J., Schiffelers, R. R. H., & Lensink, L. (2018). Software process analysis methodology-a methodology based on lessons learned in embracing legacy software. In Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018 (blz. 665-674). Artikel 8530079 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICSME.2018.00076

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title = "Software process analysis methodology-a methodology based on lessons learned in embracing legacy software",

abstract = "Over the last decades, the complexity of high-Tech systems, and the software systems controlling them, has increased considerably. In practice, it is hard to keep knowledge and documentation of these ever-evolving software systems up-To-date with their actual realization; we are dealing with legacy software. Clearly, this lack of knowledge, insight, and understanding is more and more becoming a critical issue. Process mining provides an interesting opportunity to improve understanding and analyze software behavior based on observations from the system on the run. However, a concrete software process analysis methodology was lacking. This paper 1) discusses a software process analysis case study at ASML, a large high-Tech company, and, based on the lessons learned, 2) presents a concrete methodology for analyzing software processes. The presented methodology actively includes the system under analysis and is based on practical experiences in applying process mining on industrial-scale legacy software.",

keywords = "Case Study, Methodology, Model-Driven Analysis, Passive Learning, Performance Analysis, Process Mining, Program Analysis, Reverse Engineering",

author = "Maikel Leemans and \{van der Aalst\}, \{Wil M.P.\} and \{van den Brand\}, \{Mark G.J.\} and Schiffelers, \{Ramon R.H.\} and Leonard Lensink",

year = "2018",

month = nov,

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doi = "10.1109/ICSME.2018.00076",

language = "English",

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note = "34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018), ICSME ; Conference date: 23-09-2018 Through 29-09-2018",

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Leemans, M, van der Aalst, WMP, van den Brand, MGJ, Schiffelers, RRH & Lensink, L 2018, Software process analysis methodology-a methodology based on lessons learned in embracing legacy software. in Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018., 8530079, Institute of Electrical and Electronics Engineers, Piscataway, blz. 665-674, 34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018), Madrid, Spanje, 23/09/18. https://doi.org/10.1109/ICSME.2018.00076

Software process analysis methodology-a methodology based on lessons learned in embracing legacy software. / Leemans, Maikel; van der Aalst, Wil M.P.; van den Brand, Mark G.J. et al.
Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. Piscataway: Institute of Electrical and Electronics Engineers, 2018. blz. 665-674 8530079.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AU - Leemans, Maikel

AU - van der Aalst, Wil M.P.

AU - van den Brand, Mark G.J.

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AU - Lensink, Leonard

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N2 - Over the last decades, the complexity of high-Tech systems, and the software systems controlling them, has increased considerably. In practice, it is hard to keep knowledge and documentation of these ever-evolving software systems up-To-date with their actual realization; we are dealing with legacy software. Clearly, this lack of knowledge, insight, and understanding is more and more becoming a critical issue. Process mining provides an interesting opportunity to improve understanding and analyze software behavior based on observations from the system on the run. However, a concrete software process analysis methodology was lacking. This paper 1) discusses a software process analysis case study at ASML, a large high-Tech company, and, based on the lessons learned, 2) presents a concrete methodology for analyzing software processes. The presented methodology actively includes the system under analysis and is based on practical experiences in applying process mining on industrial-scale legacy software.

AB - Over the last decades, the complexity of high-Tech systems, and the software systems controlling them, has increased considerably. In practice, it is hard to keep knowledge and documentation of these ever-evolving software systems up-To-date with their actual realization; we are dealing with legacy software. Clearly, this lack of knowledge, insight, and understanding is more and more becoming a critical issue. Process mining provides an interesting opportunity to improve understanding and analyze software behavior based on observations from the system on the run. However, a concrete software process analysis methodology was lacking. This paper 1) discusses a software process analysis case study at ASML, a large high-Tech company, and, based on the lessons learned, 2) presents a concrete methodology for analyzing software processes. The presented methodology actively includes the system under analysis and is based on practical experiences in applying process mining on industrial-scale legacy software.

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KW - Methodology

KW - Model-Driven Analysis

KW - Passive Learning

KW - Performance Analysis

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KW - Program Analysis

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Leemans M, van der Aalst WMP, van den Brand MGJ, Schiffelers RRH, Lensink L. Software process analysis methodology-a methodology based on lessons learned in embracing legacy software. In Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. Piscataway: Institute of Electrical and Electronics Engineers. 2018. blz. 665-674. 8530079 doi: 10.1109/ICSME.2018.00076

Software process analysis methodology-a methodology based on lessons learned in embracing legacy software

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