A Configurable Software Model of a Self-Adaptive Robotic System

Self-adaptation, meant to increase reliability, is a crucial feature of cyber-physical systems operating in uncertain physical environments. Ensuring safety properties of self-adaptive systems is of utter importance, especially when operating in remote environments where communication with a human operator is limited, like under water or in space. This paper presents a software model that allows the analysis of one such self-adaptive system, a configurable underwater robot used for pipeline inspection, by means of the probabilistic model checker ProFeat. Furthermore, it shows that the configurable software model is easily extensible to further, possibly more complex use cases and analyses.

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Publication Details

Journal
Science of Computer Programming
Published
2024-10-17
DOI
https://doi.org/10.1016/j.scico.2024.103221
Citations
4
Primary Topic
Advanced Software Engineering Methodologies
Type
article
Field-Weighted Citation Impact
1.39

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article

A Configurable Software Model of a Self-Adaptive Robotic System

Silvia Lizeth Tapia Tarifa, Juliane Päßler, Einar Broch Johnsen, Maurice H. ter Beek et al.
4 citations
Science of Computer Programming
Advanced Software Engineering Methodologies
1.39
article

A Configurable Software Model of a Self-Adaptive Robotic System

Silvia Lizeth Tapia Tarifa, Juliane Päßler, Einar Broch Johnsen, Maurice H. ter Beek, Ferruccio Damiani
article en
4 citations

Abstract

Self-adaptation, meant to increase reliability, is a crucial feature of cyber-physical systems operating in uncertain physical environments. Ensuring safety properties of self-adaptive systems is of utter importance, especially when operating in remote environments where communication with a human operator is limited, like under water or in space. This paper presents a software model that allows the analysis of one such self-adaptive system, a configurable underwater robot used for pipeline inspection, by means of the probabilistic model checker ProFeat. Furthermore, it shows that the configurable software model is easily extensible to further, possibly more complex use cases and analyses.

Science of Computer ProgrammingVol. 240
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" (IT), University of Oslo (NO), Museo Egizio (IT), University of Turin (IT)
Ministero dell'Università e della Ricerca, Horizon 2020 Framework Programme
Openalex Percentile: Top 15%
Advanced Software Engineering Methodologies
1.39
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