Bad Smells in Industrial Automation: Sniffing out Feature Envy

Rick Rabiser; Lisa Sonnleithner; Alois Zoitl

doi:10.1109/SEAA56994.2022.00061

Bad Smells in Industrial Automation: Sniffing out Feature Envy

LIT Cyber-Physical Systems Lab

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

Abstract

Bad Smells are sub-optimal software structures or patterns. They can obstruct the understandability of a software system and cause maintenance issues. As a result, it is critical to avoid Bad Smells. While the subject is well-researched in software engineering, it remains an unresolved issue in industrial automation, e.g., when developing control software in the context of a Cyber-Physical Production System (CPPS). In this short paper, we present possible detection methods for Feature Envy, a smell that indicates bad modularization of a software system. We explain how these methods can be applied to analyze control software developed in IEC 61499. We present first results as well as next steps.

Originalsprache	Englisch
Titel	Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022
Herausgeber*innen	Gustavo M. Callico, Regina Hebig, Andreas Wortmann
Erscheinungsort	New York City, USA
Verlag	IEEE
Seiten	346-349
Seitenumfang	4
ISBN (elektronisch)	9781665461528
ISBN (Print)	978-1-6654-6152-8
DOIs	https://doi.org/10.1109/SEAA56994.2022.00061
Publikationsstatus	Veröffentlicht - Aug. 2022

Publikationsreihe

Name	Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 9 – Industrie, Innovation und Infrastruktur

Wissenschaftszweige

202017 Embedded Systems
102022 Softwareentwicklung
102025 Verteilte Systeme
102029 Praktische Informatik
202003 Automatisierungstechnik
202041 Technische Informatik
102 Informatik

JKU-Schwerpunkte

Digital Transformation

Zugriff auf Dokument

10.1109/SEAA56994.2022.00061

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Christian Doppler Laboratory for Mastering Variability in Software-intensive Cyber-physical Production Systems (CDL VaSiCS)
Bauer, P. (Forscher*in), Fadhlillah, H. (Forscher*in), Gutierrez, A. (Forscher*in), Kutsia, E. (Forscher*in), Sharma, S. (Forscher*in), Sonnleithner, L. (Forscher*in), Unterdechler, M. (Forscher*in), Rabiser, R. (Projektleiter*in) & Zoitl, A. (Projektleiter*in)
01.02.2021 → 31.01.2028
Projekt: Geförderte Forschung › CDG - Christian Doppler Forschungsgesellschaft

Dieses zitieren

Rabiser, R., Sonnleithner, L., & Zoitl, A. (2022). Bad Smells in Industrial Automation: Sniffing out Feature Envy. in G. M. Callico, R. Hebig, & A. Wortmann (Hrsg.), Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022 (S. 346-349). (Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022). IEEE. https://doi.org/10.1109/SEAA56994.2022.00061

Rabiser, Rick ; Sonnleithner, Lisa ; Zoitl, Alois. / Bad Smells in Industrial Automation: Sniffing out Feature Envy. Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022. Hrsg. / Gustavo M. Callico ; Regina Hebig ; Andreas Wortmann. New York City, USA : IEEE, 2022. S. 346-349 (Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022).

@inproceedings{204c4e3261a04defbf9923240d73bc22,

title = "Bad Smells in Industrial Automation: Sniffing out Feature Envy",

abstract = "Bad Smells are sub-optimal software structures or patterns. They can obstruct the understandability of a software system and cause maintenance issues. As a result, it is critical to avoid Bad Smells. While the subject is well-researched in software engineering, it remains an unresolved issue in industrial automation, e.g., when developing control software in the context of a Cyber-Physical Production System (CPPS). In this short paper, we present possible detection methods for Feature Envy, a smell that indicates bad modularization of a software system. We explain how these methods can be applied to analyze control software developed in IEC 61499. We present first results as well as next steps.",

keywords = "IEC 61499, measure, metric, bad smell, CPS, Feature Envy, code smell, distributed control system, anti-pattern, design smell, CPPS",

author = "Rick Rabiser and Lisa Sonnleithner and Alois Zoitl",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.",

year = "2022",

month = aug,

doi = "10.1109/SEAA56994.2022.00061",

language = "English",

isbn = "978-1-6654-6152-8",

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editor = "Callico, \{Gustavo M.\} and Regina Hebig and Andreas Wortmann",

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Rabiser, R , Sonnleithner, L & Zoitl, A 2022, Bad Smells in Industrial Automation: Sniffing out Feature Envy. in GM Callico, R Hebig & A Wortmann (Hrsg.), Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022. Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022, IEEE, New York City, USA, S. 346-349. https://doi.org/10.1109/SEAA56994.2022.00061

Bad Smells in Industrial Automation: Sniffing out Feature Envy. / Rabiser, Rick ; Sonnleithner, Lisa ; Zoitl, Alois.
Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022. Hrsg. / Gustavo M. Callico; Regina Hebig; Andreas Wortmann. New York City, USA: IEEE, 2022. S. 346-349 (Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022).

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Bad Smells in Industrial Automation: Sniffing out Feature Envy

AU - Rabiser, Rick

AU - Sonnleithner, Lisa

AU - Zoitl, Alois

PY - 2022/8

Y1 - 2022/8

N2 - Bad Smells are sub-optimal software structures or patterns. They can obstruct the understandability of a software system and cause maintenance issues. As a result, it is critical to avoid Bad Smells. While the subject is well-researched in software engineering, it remains an unresolved issue in industrial automation, e.g., when developing control software in the context of a Cyber-Physical Production System (CPPS). In this short paper, we present possible detection methods for Feature Envy, a smell that indicates bad modularization of a software system. We explain how these methods can be applied to analyze control software developed in IEC 61499. We present first results as well as next steps.

AB - Bad Smells are sub-optimal software structures or patterns. They can obstruct the understandability of a software system and cause maintenance issues. As a result, it is critical to avoid Bad Smells. While the subject is well-researched in software engineering, it remains an unresolved issue in industrial automation, e.g., when developing control software in the context of a Cyber-Physical Production System (CPPS). In this short paper, we present possible detection methods for Feature Envy, a smell that indicates bad modularization of a software system. We explain how these methods can be applied to analyze control software developed in IEC 61499. We present first results as well as next steps.

KW - IEC 61499

KW - measure

KW - metric

KW - bad smell

KW - CPS

KW - Feature Envy

KW - code smell

KW - distributed control system

KW - anti-pattern

KW - design smell

KW - CPPS

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U2 - 10.1109/SEAA56994.2022.00061

DO - 10.1109/SEAA56994.2022.00061

M3 - Conference proceedings

SN - 978-1-6654-6152-8

T3 - Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022

SP - 346

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BT - Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022

A2 - Callico, Gustavo M.

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Rabiser R , Sonnleithner L , Zoitl A. Bad Smells in Industrial Automation: Sniffing out Feature Envy. in Callico GM, Hebig R, Wortmann A, Hrsg., Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022. New York City, USA: IEEE. 2022. S. 346-349. (Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022). doi: 10.1109/SEAA56994.2022.00061

Bad Smells in Industrial Automation: Sniffing out Feature Envy

Abstract

Publikationsreihe

UN SDGs

Wissenschaftszweige

JKU-Schwerpunkte

Zugriff auf Dokument

Andere Dateien und Links

Projekte

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

Dieses zitieren