STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project

Edilton Lima dos Santos; Gilles Perrouin; Pierre Yves Schobbens

doi:10.1145/3377024.3377033

STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project

Edilton Lima dos Santos, Gilles Perrouin, Pierre Yves Schobbens

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférence › Article dans les actes d'une conférence/un colloque

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Résumé

Dynamically Adaptive Systems (DAS) modify their behaviours in response to (sometimes unpredictable) changes in their environment or to the evolution of their own abilities (sensors and actuators). To support adaptation, a reference architecture (such as the MAPE-K model) is paramount. Yet, this is not sufficient as challenges concerning the fine-grained variability management and testability remain. The STARS Ph.D. project aims at developing a variability and context-aware architectural model for DAS that particularly takes into account testability. In particular, we want to adapt tests at runtime in order to assess and prevent the impact of inappropriate adaptations.

langue originale	Anglais
titre	Proceedings - VaMoS 2020
Sous-titre	14th International Working Conference on Variability Modelling of Software-Intensive Systems
rédacteurs en chef	Maxime Cordy, Mathieu Acher, Danilo Beuche, Gunter Saake
Editeur	ACM Press
Pages	1-2
Nombre de pages	2
ISBN (Electronique)	9781450375016
Les DOIs	https://doi.org/10.1145/3377024.3377033
Etat de la publication	Publié - 5 févr. 2020
Evénement	14th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2020 - Magdeburg, Allemagne Durée: 5 févr. 2020 → 7 févr. 2020

Série de publications

Nom	PervasiveHealth: Pervasive Computing Technologies for Healthcare
ISSN (imprimé)	2153-1633

Une conférence

Une conférence	14th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2020
Pays/Territoire	Allemagne
La ville	Magdeburg
période	5/02/20 → 7/02/20

Accès au document

10.1145/3377024.3377033

STARS_Software_Technology_for_Adaptable_and_Reusable_Systems_PhD_Research_Project_1Accepted author manuscript, 350 KB

Autres fichiers et liens

Link to publication in Scopus

1 Participation à une conférence, un congrès
1 Présentation orale

STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project
Lima dos Santos, E. (Orateur)
févr. 2020
Activité: Discours ou présentation › Présentation orale
14th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2020
Lima dos Santos, E. (Orateur)
2020
Activité: Participation ou organisation d'un événement › Participation à une conférence, un congrès

Behavioral Maps: A Framework to Assess and Validate Self-Adaptive Architectures at Runtime
Lima dos Santos, E. (Auteur)Perrouin, G. (Promoteur), Schobbens, P.-Y. (Promoteur), Remiche, M.-A. (Président), Englebert, V. (Jury), Mens, K. (Jury) & Raibulet, C. (Jury), 12 sept. 2023
Student thesis: Doc types › Docteur en Sciences

Fichier

Contient cette citation

Lima dos Santos, E., Perrouin, G., & Schobbens, P. Y. (2020). STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project. Dans M. Cordy, M. Acher, D. Beuche, & G. Saake (eds.), Proceedings - VaMoS 2020: 14th International Working Conference on Variability Modelling of Software-Intensive Systems (p. 1-2). Article a15 (PervasiveHealth: Pervasive Computing Technologies for Healthcare). ACM Press. https://doi.org/10.1145/3377024.3377033

Lima dos Santos, Edilton ; Perrouin, Gilles ; Schobbens, Pierre Yves. / STARS : Software Technology for Adaptable and Reusable Systems PhD Research Project. Proceedings - VaMoS 2020: 14th International Working Conference on Variability Modelling of Software-Intensive Systems. Editeur / Maxime Cordy ; Mathieu Acher ; Danilo Beuche ; Gunter Saake. ACM Press, 2020. p. 1-2 (PervasiveHealth: Pervasive Computing Technologies for Healthcare).

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abstract = "Dynamically Adaptive Systems (DAS) modify their behaviours in response to (sometimes unpredictable) changes in their environment or to the evolution of their own abilities (sensors and actuators). To support adaptation, a reference architecture (such as the MAPE-K model) is paramount. Yet, this is not sufficient as challenges concerning the fine-grained variability management and testability remain. The STARS Ph.D. project aims at developing a variability and context-aware architectural model for DAS that particularly takes into account testability. In particular, we want to adapt tests at runtime in order to assess and prevent the impact of inappropriate adaptations.",

keywords = "MAPE-K loop, Self-adapting, Software architecture, Software test",

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

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Lima dos Santos, E , Perrouin, G & Schobbens, PY 2020, STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project. Dans M Cordy, M Acher, D Beuche & G Saake (eds), Proceedings - VaMoS 2020: 14th International Working Conference on Variability Modelling of Software-Intensive Systems., a15, PervasiveHealth: Pervasive Computing Technologies for Healthcare, ACM Press, p. 1-2, 14th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2020, Magdeburg, Allemagne, 5/02/20. https://doi.org/10.1145/3377024.3377033

STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project. / Lima dos Santos, Edilton ; Perrouin, Gilles ; Schobbens, Pierre Yves.
Proceedings - VaMoS 2020: 14th International Working Conference on Variability Modelling of Software-Intensive Systems. Ed. / Maxime Cordy; Mathieu Acher; Danilo Beuche; Gunter Saake. ACM Press, 2020. p. 1-2 a15 (PervasiveHealth: Pervasive Computing Technologies for Healthcare).

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférence › Article dans les actes d'une conférence/un colloque

TY - GEN

T1 - STARS

T2 - 14th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2020

AU - Lima dos Santos, Edilton

AU - Perrouin, Gilles

AU - Schobbens, Pierre Yves

PY - 2020/2/5

Y1 - 2020/2/5

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AB - Dynamically Adaptive Systems (DAS) modify their behaviours in response to (sometimes unpredictable) changes in their environment or to the evolution of their own abilities (sensors and actuators). To support adaptation, a reference architecture (such as the MAPE-K model) is paramount. Yet, this is not sufficient as challenges concerning the fine-grained variability management and testability remain. The STARS Ph.D. project aims at developing a variability and context-aware architectural model for DAS that particularly takes into account testability. In particular, we want to adapt tests at runtime in order to assess and prevent the impact of inappropriate adaptations.

KW - MAPE-K loop

KW - Self-adapting

KW - Software architecture

KW - Software test

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T3 - PervasiveHealth: Pervasive Computing Technologies for Healthcare

SP - 1

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BT - Proceedings - VaMoS 2020

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A2 - Acher, Mathieu

A2 - Beuche, Danilo

A2 - Saake, Gunter

PB - ACM Press

Y2 - 5 February 2020 through 7 February 2020

ER -

Lima dos Santos E , Perrouin G , Schobbens PY. STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project. Dans Cordy M, Acher M, Beuche D, Saake G, rédacteurs en chef, Proceedings - VaMoS 2020: 14th International Working Conference on Variability Modelling of Software-Intensive Systems. ACM Press. 2020. p. 1-2. a15. (PervasiveHealth: Pervasive Computing Technologies for Healthcare). doi: 10.1145/3377024.3377033

STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project

Résumé

Série de publications

Une conférence

Accès au document

Autres fichiers et liens

Empreinte digitale

Activités

STARS: Software Technology for Adaptable and Reusable Systems PhD Research Project

14th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2020

Thèses de l'étudiant

Behavioral Maps: A Framework to Assess and Validate Self-Adaptive Architectures at Runtime

Contient cette citation