Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software

Philipp Bauer; Lisa Sonnleithner; Elene Kutsia; Rick Rabiser; Alois Zoitl

doi:10.1109/ETFA54631.2023.10275726

Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software

LIT Cyber-Physical Systems Lab

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

Abstract

Software size and complexity in all kinds of domains increase rapidly in recent times, making software maintenance and reusability increasingly difficult. Analysis of existing software and subsequent re-modularization can help with these challenges. Although software re-modularization can be time- and resource-intensive, it can support engineers in improving the quality of their systems in the future. Code can contain certain patterns, such as code smells, that define some kind of problematic implementation that is usually inefficient and hinders future development. We explore the use of a semantic clustering algorithm, which aims to minimize the code smell "Feature Envy". We apply this algorithm recursively to create a multi-level hierarchy. With this approach, we explore the re-modularization of existing IEC 61499 control systems. First tests we conducted on example implementations of a capping station and a real-life-sized industrial control system show a significant reduction of Feature Envy and thus the coupling between modules using this approach.

Original language	English
Title of host publication	Proceedings of the 28th IEEE IES International Conference on Emerging Technologies and Factory Automation (ETFA 2023)
Place of Publication	New York, NY, United States
Publisher	IEEE
Pages	1-4
Number of pages	4
ISBN (Electronic)	9798350339918
ISBN (Print)	979-8-3503-3991-8
DOIs	https://doi.org/10.1109/ETFA54631.2023.10275726
Publication status	Published - Oct 2023

Publication series

Name	IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume	2023-September
ISSN (Print)	1946-0740
ISSN (Electronic)	1946-0759

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Fields of science

202017 Embedded systems
102022 Software development
102025 Distributed systems
102029 Practical computer science
202003 Automation
202041 Computer engineering

JKU Focus areas

Digital Transformation

Access to Document

10.1109/ETFA54631.2023.10275726

Cite this

Bauer, P., Sonnleithner, L., Kutsia, E., Rabiser, R., & Zoitl, A. (2023). Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software. In Proceedings of the 28th IEEE IES International Conference on Emerging Technologies and Factory Automation (ETFA 2023) (pp. 1-4). (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA; Vol. 2023-September). IEEE. https://doi.org/10.1109/ETFA54631.2023.10275726

Bauer, Philipp ; Sonnleithner, Lisa ; Kutsia, Elene et al. / Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software. Proceedings of the 28th IEEE IES International Conference on Emerging Technologies and Factory Automation (ETFA 2023). New York, NY, United States : IEEE, 2023. pp. 1-4 (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA).

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title = "Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software",

abstract = "Software size and complexity in all kinds of domains increase rapidly in recent times, making software maintenance and reusability increasingly difficult. Analysis of existing software and subsequent re-modularization can help with these challenges. Although software re-modularization can be time- and resource-intensive, it can support engineers in improving the quality of their systems in the future. Code can contain certain patterns, such as code smells, that define some kind of problematic implementation that is usually inefficient and hinders future development. We explore the use of a semantic clustering algorithm, which aims to minimize the code smell {"}Feature Envy{"}. We apply this algorithm recursively to create a multi-level hierarchy. With this approach, we explore the re-modularization of existing IEC 61499 control systems. First tests we conducted on example implementations of a capping station and a real-life-sized industrial control system show a significant reduction of Feature Envy and thus the coupling between modules using this approach.",

keywords = "clustering algorithms, code smells, cohesion, control software, coupling, IEC 614499, modularization",

author = "Philipp Bauer and Lisa Sonnleithner and Elene Kutsia and Rick Rabiser and Alois Zoitl",

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year = "2023",

month = oct,

doi = "10.1109/ETFA54631.2023.10275726",

language = "English",

isbn = "979-8-3503-3991-8",

series = "IEEE International Conference on Emerging Technologies and Factory Automation, ETFA",

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Bauer, P, Sonnleithner, L , Kutsia, E , Rabiser, R & Zoitl, A 2023, Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software. in Proceedings of the 28th IEEE IES International Conference on Emerging Technologies and Factory Automation (ETFA 2023). IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, vol. 2023-September, IEEE, New York, NY, United States, pp. 1-4. https://doi.org/10.1109/ETFA54631.2023.10275726

Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software. / Bauer, Philipp; Sonnleithner, Lisa ; Kutsia, Elene et al.
Proceedings of the 28th IEEE IES International Conference on Emerging Technologies and Factory Automation (ETFA 2023). New York, NY, United States: IEEE, 2023. p. 1-4 (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA; Vol. 2023-September).

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

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T1 - Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software

AU - Bauer, Philipp

AU - Sonnleithner, Lisa

AU - Kutsia, Elene

AU - Rabiser, Rick

AU - Zoitl, Alois

PY - 2023/10

Y1 - 2023/10

N2 - Software size and complexity in all kinds of domains increase rapidly in recent times, making software maintenance and reusability increasingly difficult. Analysis of existing software and subsequent re-modularization can help with these challenges. Although software re-modularization can be time- and resource-intensive, it can support engineers in improving the quality of their systems in the future. Code can contain certain patterns, such as code smells, that define some kind of problematic implementation that is usually inefficient and hinders future development. We explore the use of a semantic clustering algorithm, which aims to minimize the code smell "Feature Envy". We apply this algorithm recursively to create a multi-level hierarchy. With this approach, we explore the re-modularization of existing IEC 61499 control systems. First tests we conducted on example implementations of a capping station and a real-life-sized industrial control system show a significant reduction of Feature Envy and thus the coupling between modules using this approach.

AB - Software size and complexity in all kinds of domains increase rapidly in recent times, making software maintenance and reusability increasingly difficult. Analysis of existing software and subsequent re-modularization can help with these challenges. Although software re-modularization can be time- and resource-intensive, it can support engineers in improving the quality of their systems in the future. Code can contain certain patterns, such as code smells, that define some kind of problematic implementation that is usually inefficient and hinders future development. We explore the use of a semantic clustering algorithm, which aims to minimize the code smell "Feature Envy". We apply this algorithm recursively to create a multi-level hierarchy. With this approach, we explore the re-modularization of existing IEC 61499 control systems. First tests we conducted on example implementations of a capping station and a real-life-sized industrial control system show a significant reduction of Feature Envy and thus the coupling between modules using this approach.

KW - clustering algorithms

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ER -

Bauer P, Sonnleithner L , Kutsia E , Rabiser R , Zoitl A. Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software. In Proceedings of the 28th IEEE IES International Conference on Emerging Technologies and Factory Automation (ETFA 2023). New York, NY, United States: IEEE. 2023. p. 1-4. (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA). doi: 10.1109/ETFA54631.2023.10275726

Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software

Abstract

Publication series

UN SDGs

Fields of science

JKU Focus areas

Access to Document

Other files and links

Christian Doppler Laboratory for Mastering Variability in Software-intensive Cyber-physical Production Systems (CDL VaSiCS)

Cite this

Using Graph Clustering Algorithms to Modularize IEC 61499 Control Software

Abstract

Publication series

UN SDGs

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

Christian Doppler Laboratory for Mastering Variability in Software-intensive Cyber-physical Production Systems (CDL VaSiCS)

Cite this