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

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

7 Citations (Scopus)

2 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	665-674
Number of pages	10
ISBN (Electronic)	978-1-5386-7870-1
ISBN (Print)	978-1-5386-7871-8
DOIs	https://doi.org/10.1109/ICSME.2018.00076
Publication status	Published - 9 Nov 2018
Event	34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018) - Madrid, Spain Duration: 23 Sept 2018 → 29 Sept 2018 Conference number: 34

Conference

Conference	34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018)
Abbreviated title	ICSME
Country/Territory	Spain
City	Madrid
Period	23/09/18 → 29/09/18

Keywords

Case Study
Methodology
Model-Driven Analysis
Passive Learning
Performance Analysis
Process Mining
Program Analysis
Reverse Engineering

Access to Document

10.1109/ICSME.2018.00076

Cite this

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 (pp. 665-674). Article 8530079 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICSME.2018.00076

@inproceedings{f1618bcf27a847efac22b27775a2cdd6,

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,

day = "9",

doi = "10.1109/ICSME.2018.00076",

language = "English",

isbn = "978-1-5386-7871-8",

pages = "665--674",

booktitle = "Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

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

}

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, pp. 665-674, 34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018), Madrid, Spain, 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. p. 665-674 8530079.

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

TY - GEN

T1 - Software process analysis methodology-a methodology based on lessons learned in embracing legacy software

AU - Leemans, Maikel

AU - van der Aalst, Wil M.P.

AU - van den Brand, Mark G.J.

AU - Schiffelers, Ramon R.H.

AU - Lensink, Leonard

N1 - Conference code: 34

PY - 2018/11/9

Y1 - 2018/11/9

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.

KW - Case Study

KW - Methodology

KW - Model-Driven Analysis

KW - Passive Learning

KW - Performance Analysis

KW - Process Mining

KW - Program Analysis

KW - Reverse Engineering

UR - http://www.scopus.com/inward/record.url?scp=85058297009&partnerID=8YFLogxK

U2 - 10.1109/ICSME.2018.00076

DO - 10.1109/ICSME.2018.00076

M3 - Conference contribution

AN - SCOPUS:85058297009

SN - 978-1-5386-7871-8

SP - 665

EP - 674

BT - Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 34th IEEE International Conference on Software Maintenance and Evolution (ICSME 2018)

Y2 - 23 September 2018 through 29 September 2018

ER -

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. p. 665-674. 8530079 doi: 10.1109/ICSME.2018.00076

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

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this