research-article

Towards a domain-specific modeling language for self-adaptive systems conceptual modeling

Authors:

João Pablo S. da Silva,

Marcelo S. Pimenta,

Gilleanes T. A. Guedes,

Elder M. RodriguesAuthors Info & Claims

SBES '18: Proceedings of the XXXII Brazilian Symposium on Software Engineering

Pages 208 - 213

https://doi.org/10.1145/3266237.3266244

Published: 17 September 2018 Publication History

Abstract

Self-adaptive Systems (SaSs) are able to adapt their behavior at runtime in response to contextual changes. In this work, we are interested in SaSs conceptual modeling, which is the act of creating models that describe aspects of the world. SaSs modeling is a non-trivial activity because it deals with requirements uncertainty, contextual changes, and behavior adaptation. This complexity can be minimized by using Domain-Specific Modeling Languages (DSMLs), which may be created by extending Unified Modeling Language (UML). In this paper, we propose a UML profile that represents the higher-level abstractions required to provide support for SaSs conceptual modeling. We developed the UML profile by modeling the domain of interest and extending the UML class metaclass. The UML profile was evaluated through the focus group technique, which was performed by software engineering professors. As the outcome, the focus group participants considered the UML profile able to produce SaSs conceptual models with more expressiveness than UML standard.

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Cited By

Da Silva JPimenta MEcar MGiordano DChagas JOtokovieski MDias BForrati S(2023)Towards a Framework for Self-adaptive Systems Conceptual ModelingProceedings of the XIX Brazilian Symposium on Information Systems10.1145/3592813.3592921(325-331)Online publication date: 29-May-2023
https://dl.acm.org/doi/10.1145/3592813.3592921
Nawara DKashef R(2021)Context-Aware Recommendation Systems in the IoT Environment (IoT-CARS)–A Comprehensive OverviewIEEE Access10.1109/ACCESS.2021.31220989(144270-144284)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3122098
Cazzola WGhosh SAl-Refai MMaurina G(2021)Bridging the model-to-code abstraction gap with fuzzy logic in model-based regression test selectionSoftware and Systems Modeling10.1007/s10270-021-00899-6Online publication date: 21-Jul-2021
https://doi.org/10.1007/s10270-021-00899-6
Show More Cited By

Index Terms

Towards a domain-specific modeling language for self-adaptive systems conceptual modeling
1. Software and its engineering
  1. Software creation and management
    1. Designing software

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cover image ACM Other conferences

SBES '18: Proceedings of the XXXII Brazilian Symposium on Software Engineering

September 2018

379 pages

ISBN:9781450365031

DOI:10.1145/3266237

Program Chairs:
Uirá Kulesza
UFRN
,
Rafael Prikladnicki
PUCRS
,
Marco Aurélio Gerosa
Northern Arizona University
,
Claudia Werner
COPPE/UFRJ
,
Rossana Andrade
UFC

Copyright © 2018 ACM.

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Published: 17 September 2018

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SBES '18

SBES '18: XXXII BRAZILIAN SYMPOSIUM ON SOFTWARE ENGINEERING

September 17 - 21, 2018

Sao Carlos, Brazil

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SBES '18 Paper Acceptance Rate 38 of 140 submissions, 27%;

Overall Acceptance Rate 147 of 427 submissions, 34%

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Cited By

Da Silva JPimenta MEcar MGiordano DChagas JOtokovieski MDias BForrati S(2023)Towards a Framework for Self-adaptive Systems Conceptual ModelingProceedings of the XIX Brazilian Symposium on Information Systems10.1145/3592813.3592921(325-331)Online publication date: 29-May-2023
https://dl.acm.org/doi/10.1145/3592813.3592921
Nawara DKashef R(2021)Context-Aware Recommendation Systems in the IoT Environment (IoT-CARS)–A Comprehensive OverviewIEEE Access10.1109/ACCESS.2021.31220989(144270-144284)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3122098
Cazzola WGhosh SAl-Refai MMaurina G(2021)Bridging the model-to-code abstraction gap with fuzzy logic in model-based regression test selectionSoftware and Systems Modeling10.1007/s10270-021-00899-6Online publication date: 21-Jul-2021
https://doi.org/10.1007/s10270-021-00899-6
Bezerra Jde Souza CMachado ISouza RMaciel RSant'Anna C(2019)smAR2tProceedings of the XXXIII Brazilian Symposium on Software Engineering10.1145/3350768.3353818(124-129)Online publication date: 23-Sep-2019
https://dl.acm.org/doi/10.1145/3350768.3353818

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