Architectural Bad Smells for Self-Adaptive Systems: Go Runtime!

Edilton Lima dos Santos; Pierre-Yves Schobbens; Ivan Machado; Gilles Perrouin

doi:10.1145/3571788.3571802

Architectural Bad Smells for Self-Adaptive Systems: Go Runtime!

Edilton Lima dos Santos, Pierre-Yves Schobbens, Ivan Machado, Gilles Perrouin

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

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Abstract

Self-adaptive systems (SAS) change their behavior and structure at runtime depending on environmental changes or user requests. For this purpose, the SASs combine architectural fragments or solutions in their adaptation process. However, this process may negatively impact the system’s architectural qualities, exhibiting architectural bad smells (ABS). Current studies perform ABS detection for SAS at design time, ignoring their intrinsic runtime variability. We demonstrate that this ignorance leads to inaccurate smell detections and possibly wrong maintenance decisions. We delineate the challenges runtime variability raise on ABS detection and argue that we should analyze SAS architectures at runtime.

Original language	English
Title of host publication	Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023
Subtitle of host publication	17th International Working Conference on Variability Modelling of Software-Intensive Systems
Editors	Myra B. Cohen, Thomas Thüm, Jacopo Mauro
Publisher	ACM Press
Pages	85-87
Number of pages	3
ISBN (Electronic)	9798400700019
DOIs	https://doi.org/10.1145/3571788.3571802
Publication status	Published - 25 Jan 2023

Publication series

Name	ACM International Conference Proceeding Series

Keywords

Architectural Quality
Architectural Smells
Runtime Validation.
Self-Adaptive Systems
Software architecture

UN SDGs

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

Access to Document

10.1145/3571788.3571802

VaMoS2023-ABS-GO-RUNTIMEAccepted author manuscript, 471 KBLicence: Other

Cite this

Santos, E. L. D., Schobbens, P.-Y., Machado, I., & Perrouin, G. (2023). Architectural Bad Smells for Self-Adaptive Systems: Go Runtime! In M. B. Cohen, T. Thüm, & J. Mauro (Eds.), Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023: 17th International Working Conference on Variability Modelling of Software-Intensive Systems (pp. 85-87). (ACM International Conference Proceeding Series). ACM Press. https://doi.org/10.1145/3571788.3571802

Santos, Edilton Lima dos ; Schobbens, Pierre-Yves ; Machado, Ivan et al. / Architectural Bad Smells for Self-Adaptive Systems : Go Runtime!. Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023: 17th International Working Conference on Variability Modelling of Software-Intensive Systems. editor / Myra B. Cohen ; Thomas Thüm ; Jacopo Mauro. ACM Press, 2023. pp. 85-87 (ACM International Conference Proceeding Series).

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title = "Architectural Bad Smells for Self-Adaptive Systems: Go Runtime!",

abstract = "Self-adaptive systems (SAS) change their behavior and structure at runtime depending on environmental changes or user requests. For this purpose, the SASs combine architectural fragments or solutions in their adaptation process. However, this process may negatively impact the system{\textquoteright}s architectural qualities, exhibiting architectural bad smells (ABS). Current studies perform ABS detection for SAS at design time, ignoring their intrinsic runtime variability. We demonstrate that this ignorance leads to inaccurate smell detections and possibly wrong maintenance decisions. We delineate the challenges runtime variability raise on ABS detection and argue that we should analyze SAS architectures at runtime.",

keywords = "Architectural Quality, Architectural Smells, Runtime Validation., Self-Adaptive Systems, Software architecture",

author = "Santos, {Edilton Lima dos} and Pierre-Yves Schobbens and Ivan Machado and Gilles Perrouin",

note = "Funding Information: Edilton Lima dos Santos is funded by a CERUNA grant from the University of Namur. Gilles Perrouin is an FNRS Research Associate. This work was partly funded by the ERDF IDEES Co-innovation project, and partly funded by the Coordena{\c c}{\~a}o de Aperfei{\c c}oamento de Pessoal de N{\'i}vel Superior - Brasil (CAPES) - Finance Code 001. Publisher Copyright: {\textcopyright} 2023 ACM.",

year = "2023",

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day = "25",

doi = "10.1145/3571788.3571802",

language = "English",

series = "ACM International Conference Proceeding Series",

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editor = "Cohen, {Myra B.} and Thomas Th{\"u}m and Jacopo Mauro",

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Santos, ELD , Schobbens, P-Y, Machado, I & Perrouin, G 2023, Architectural Bad Smells for Self-Adaptive Systems: Go Runtime! in MB Cohen, T Thüm & J Mauro (eds), Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023: 17th International Working Conference on Variability Modelling of Software-Intensive Systems. ACM International Conference Proceeding Series, ACM Press, pp. 85-87. https://doi.org/10.1145/3571788.3571802

Architectural Bad Smells for Self-Adaptive Systems: Go Runtime! / Santos, Edilton Lima dos ; Schobbens, Pierre-Yves; Machado, Ivan et al.
Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023: 17th International Working Conference on Variability Modelling of Software-Intensive Systems. ed. / Myra B. Cohen; Thomas Thüm; Jacopo Mauro. ACM Press, 2023. p. 85-87 (ACM International Conference Proceeding Series).

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Architectural Bad Smells for Self-Adaptive Systems

T2 - Go Runtime!

AU - Santos, Edilton Lima dos

AU - Schobbens, Pierre-Yves

AU - Machado, Ivan

AU - Perrouin, Gilles

N1 - Funding Information: Edilton Lima dos Santos is funded by a CERUNA grant from the University of Namur. Gilles Perrouin is an FNRS Research Associate. This work was partly funded by the ERDF IDEES Co-innovation project, and partly funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Publisher Copyright: © 2023 ACM.

PY - 2023/1/25

Y1 - 2023/1/25

N2 - Self-adaptive systems (SAS) change their behavior and structure at runtime depending on environmental changes or user requests. For this purpose, the SASs combine architectural fragments or solutions in their adaptation process. However, this process may negatively impact the system’s architectural qualities, exhibiting architectural bad smells (ABS). Current studies perform ABS detection for SAS at design time, ignoring their intrinsic runtime variability. We demonstrate that this ignorance leads to inaccurate smell detections and possibly wrong maintenance decisions. We delineate the challenges runtime variability raise on ABS detection and argue that we should analyze SAS architectures at runtime.

AB - Self-adaptive systems (SAS) change their behavior and structure at runtime depending on environmental changes or user requests. For this purpose, the SASs combine architectural fragments or solutions in their adaptation process. However, this process may negatively impact the system’s architectural qualities, exhibiting architectural bad smells (ABS). Current studies perform ABS detection for SAS at design time, ignoring their intrinsic runtime variability. We demonstrate that this ignorance leads to inaccurate smell detections and possibly wrong maintenance decisions. We delineate the challenges runtime variability raise on ABS detection and argue that we should analyze SAS architectures at runtime.

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KW - Runtime Validation.

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M3 - Conference contribution

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EP - 87

BT - Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023

A2 - Cohen, Myra B.

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A2 - Mauro, Jacopo

PB - ACM Press

ER -

Santos ELD , Schobbens PY, Machado I, Perrouin G. Architectural Bad Smells for Self-Adaptive Systems: Go Runtime! In Cohen MB, Thüm T, Mauro J, editors, Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023: 17th International Working Conference on Variability Modelling of Software-Intensive Systems. ACM Press. 2023. p. 85-87. (ACM International Conference Proceeding Series). doi: 10.1145/3571788.3571802

Architectural Bad Smells for Self-Adaptive Systems: Go Runtime!

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Keywords

UN SDGs

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