research-article

Process Mining to Unleash Variability Management: Discovering Configuration Workflows Using Logs

Authors:

Ángel Jesús Varela-Vaca,

José A. Galindo,

Belén Ramos-Gutiérrez,

María Teresa Gómez-López,

David BenavidesAuthors Info & Claims

SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference - Volume A

Pages 265 - 276

https://doi.org/10.1145/3336294.3336303

Published: 09 September 2019 Publication History

Abstract

Variability models are used to build configurators. Configurators are programs that guide users through the configuration process to reach a desired configuration that fulfils user requirements. The same variability model can be used to design different configurators employing different techniques. One of the elements that can change in a configurator is the configuration workflow, i.e., the order and sequence in which the different configuration elements are presented to the configuration stakeholders. When developing a configurator, a challenge is to decide the configuration workflow that better suites stakeholders according to previous configurations. For example, when configuring a Linux distribution, the configuration process start by choosing the network or the graphic card, and then other packages with respect to a given sequence. In this paper, we present COnfiguration workfLOw proceSS mIning (COLOSSI), an automated technique that given a set of logs of previous configurations and a variability model can automatically assist to determine the configuration workflow that better fits the configuration logs generated by user activities. The technique is based on process discovery, commonly used in the process mining area, with an adaptation to configuration contexts. Our proposal is validated using existing data from an ERP configuration environment showing its feasibility. Furthermore, we open the door to new applications of process mining techniques in different areas of software product line engineering.

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Cited By

Fortz STemple PDevroey XHeymans PPerrouin G(2024)VaryMinions: leveraging RNNs to identify variants in variability-intensive systems’ logsEmpirical Software Engineering10.1007/s10664-024-10473-529:4Online publication date: 15-Jun-2024
https://dl.acm.org/doi/10.1007/s10664-024-10473-5
Dolak RBarcak THalaska M(2024)ERP Logs and Its Use for Process Mining Student Learning PurposesInnovative Technologies and Learning10.1007/978-3-031-65881-5_20(185-192)Online publication date: 21-Jul-2024
https://doi.org/10.1007/978-3-031-65881-5_20
Dizayee FIsmael ZBilal SHussein B(2023)Exploring the Impact of Data Mining Techniques in Healthcare and Medical Data: A Systematic Literature Review2023 9th International Engineering Conference on Sustainable Technology and Development (IEC)10.1109/IEC57380.2023.10438817(206-211)Online publication date: 21-Feb-2023
https://doi.org/10.1109/IEC57380.2023.10438817
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Index Terms

Process Mining to Unleash Variability Management: Discovering Configuration Workflows Using Logs
1. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Reusability
        Software product lines

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cover image ACM Other conferences

SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference - Volume A

September 2019

356 pages

ISBN:9781450371384

DOI:10.1145/3336294

Editors:
Thorsten Berger
Chalmers | University of Gothenburg, Sweden
,
Philippe Collet
Université Côte d'Azur, France
,
Laurence Duchien
University Lille, France
,
Thomas Fogdal
Danfoss Power Electronics A/S, Denmark
,
Patrick Heymans
University of Namur, Belgium
,
Timo Kehrer
Humboldt-Universität zu Berlin, Germany
,
Jabier Martinez
Tecnalia, Spain
,
Raúl Mazo
University Paris 1 Panthéon-Sorbonne, France
,
Leticia Montalvillo
IK4-IKERLAN Research Center, Spain
,
Camille Salinesi
University Paris 1 Panthéon-Sorbonne, France
,
Xhevahire Tërnava
Sorbonne University, France
,
Thomas Thüm
TU Braunschweig, Germany
,
Tewfik Ziadi
Sorbonne University, France

Copyright © 2019 ACM.

© 2019 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Published: 09 September 2019

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Junta de Andalucia
Cátedra de Telefónica Inteligencia en la Red
European Regional Development Fund (ERDF/FEDER)
Ministry of Science and Technology of Spain
MINECO - Juan de la Cierva postdoctoral program

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SPLC 2019

SPLC 2019: 23rd International Systems and Software Product Line Conference

September 9 - 13, 2019

Paris, France

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Cited By

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https://dl.acm.org/doi/10.1007/s10664-024-10473-5
Dolak RBarcak THalaska M(2024)ERP Logs and Its Use for Process Mining Student Learning PurposesInnovative Technologies and Learning10.1007/978-3-031-65881-5_20(185-192)Online publication date: 21-Jul-2024
https://doi.org/10.1007/978-3-031-65881-5_20
Dizayee FIsmael ZBilal SHussein B(2023)Exploring the Impact of Data Mining Techniques in Healthcare and Medical Data: A Systematic Literature Review2023 9th International Engineering Conference on Sustainable Technology and Development (IEC)10.1109/IEC57380.2023.10438817(206-211)Online publication date: 21-Feb-2023
https://doi.org/10.1109/IEC57380.2023.10438817
Estañol MVarela-Vaca ÁGómez-López MTeniente EGasca R(2022)Reasoning on the usage control security policies over data artifact business process modelsComputer Science and Information Systems10.2298/CSIS210217061E19:2(547-572)Online publication date: 2022
https://doi.org/10.2298/CSIS210217061E
Fortz STemple PDevroey XHeymans PPerrouin GAmpatzoglou AFeitosa DCatolino GLenarduzzi V(2021)VaryMinions: leveraging RNNs to identify variants in event logsProceedings of the 5th International Workshop on Machine Learning Techniques for Software Quality Evolution10.1145/3472674.3473980(13-18)Online publication date: 23-Aug-2021
https://dl.acm.org/doi/10.1145/3472674.3473980
Varela-Vaca ÁRosado DSánchez LGómez-López MGasca RFernández-Medina E(2021)CARMENComputers in Industry10.1016/j.compind.2021.103524132:COnline publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1016/j.compind.2021.103524
Vidal CFelfernig AGalindo JAtas MBenavides D(2021)Explanations for over-constrained problems using QuickXPlain with speculative executionsJournal of Intelligent Information Systems10.1007/s10844-021-00675-4Online publication date: 6-Nov-2021
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Ramos-Gutiérrez BVarela-Vaca ÁGalindo JGómez-López MBenavides D(2021)Discovering configuration workflows from existing logs using process miningEmpirical Software Engineering10.1007/s10664-020-09911-x26:1Online publication date: 26-Jan-2021
https://dl.acm.org/doi/10.1007/s10664-020-09911-x
Siek MMalik Gunadharma Mukti R(2020)Process Mining with Applications to Automotive IndustryIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/924/1/012033924(012033)Online publication date: 14-Oct-2020
https://doi.org/10.1088/1757-899X/924/1/012033
Varela-Vaca ÁRosado DSánchez LGómez-López MGasca RFernández-Medina E(2020)Definition and Verification of Security Configurations of Cyber-Physical SystemsComputer Security10.1007/978-3-030-64330-0_9(135-155)Online publication date: 17-Dec-2020
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