Lotus@Runtime: A Tool for Runtime Monitoring and Verification of Self-Adaptive Systems

Barbosa, Davi Monteiro; Lima, Rômulo Gadelha de Moura; Maia, Paulo Henrique M.; Costa, Evilásio

doi:10.1109/seams.2017.18

Cited by 26 publications

(9 citation statements)

References 19 publications

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“…In Borda et al (2018), specifications expressed in a higher-order process language for adaptive CPSs are translated to FDR (Failures-Divergences Refinement) to refinement-check requirement satisfaction. Another approach, Lotus@Runtime (Barbosa et al, 2017) addresses verification of self-adaptive systems, modelled as (probabilistic) labelled transition systems, by checking reachability properties on execution traces-which must be generated, e.g., through instrumentation or aspect-oriented techniques.…”

Section: Runtime Verification Of Self-adaptive Systemsmentioning

confidence: 99%

Adaptive distributed monitors of spatial properties for cyber–physical systems

Audrito

Casadei

Damiani

et al. 2021

Journal of Systems and Software

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Section: Runtime Verification Of Self-adaptive Systemsmentioning

confidence: 99%

Adaptive distributed monitors of spatial properties for cyber–physical systems

Audrito

Casadei

Damiani

et al. 2021

Journal of Systems and Software

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“…We assume that, after each drone movement, both battery level and distance are decreased by one unit. Steps one to four above were implemented as extensions of Lotus [7].…”

Section: A Defiant Component Identificationmentioning

confidence: 99%

Cautious Adaptation of Defiant Components

Maia

Vieira

Chagas

et al. 2019

2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)

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Systems-of-systems are formed by the composition of independently created software components. These components are designed to satisfy their individual requirements, rather than the global requirements of the systems-of-systems. We refer to components that cannot be adapted to meet both individual and global requirements as "defiant" components. In this paper, we propose a "cautious" adaptation approach which supports changing the behaviour of such defiant components under exceptional conditions to satisfy global requirements, while continuing to guarantee the satisfaction of the components' individual requirements. The approach represents both normal and exceptional conditions as scenarios; models the behaviour of exceptional conditions as wrappers implemented using an aspect-oriented technique; and deals with both single and multiple instances of defiant components with different precedence order at runtime. We evaluated an implementation of the approach using drones and boats for an organ delivery application conceived by our industrial partners, in which we assess how the proposed approach helps achieve the systemof-systems' global requirements while accommodating increased complexity of hybrid aspects such as multiplicity, precedence ordering, openness, and heterogeneity.

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“…Researchers have proposed such artifacts to develop and evaluate self-adaptation solutions, which can be categorized in two groups. (1) Artifacts that support developing and evaluating self-adaptive software and that range from requirements for the adaptive internet of things [5], component frameworks for smart cyber-physical systems [21,23], a platform for cloud applications [3], a tool for runtime monitoring and verification [2], and a benchmark environment for self-adaptive applications in Hadoop clusters [41]. (2) Several exemplars that provide a real or simulated adaptable software, on top of which adaptation engines should be developed, and that enable evaluation and comparison of adaptation engines [9,16,19,25,31,37,40].…”

Section: Introductionmentioning

confidence: 99%

“…Artifacts of the first group typically do not provide a runtime model. Exceptions are Hogna [3] and Lotus [2] that use a performance model for performance analysis respectively a labeled transition system model for verification. However, these models cannot be used for generic, architectural self-adaptation.…”

Section: Introductionmentioning

confidence: 99%

mRUBiS

Vogel

2018

Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems

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Self-adaptive software systems are often structured into an adaptation engine that manages an adaptable software by operating on a runtime model that represents the architecture of the software (model-based architectural self-adaptation). Despite the popularity of such approaches, existing exemplars provide application programming interfaces but no runtime model to develop adaptation engines. Consequently, there does not exist any exemplar that supports developing, evaluating, and comparing model-based self-adaptation off the shelf. Therefore, we present mRUBiS, an extensible exemplar for model-based architectural self-healing and self-optimization. mRUBiS simulates the adaptable software and therefore provides and maintains an architectural runtime model of the software, which can be directly used by adaptation engines to realize and perform self-adaptation. Particularly, mRUBiS supports injecting issues into the model, which should be handled by selfadaptation, and validating the model to assess the self-adaptation. Finally, mRUBiS allows developers to explore variants of adaptation engines (e.g., event-driven self-adaptation) and to evaluate the effectiveness, efficiency, and scalability of the engines. CCS CONCEPTS• Software and its engineering → Development frameworks and environments; Software development techniques;

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Lotus@Runtime: A Tool for Runtime Monitoring and Verification of Self-Adaptive Systems

Cited by 26 publications

References 19 publications

Adaptive distributed monitors of spatial properties for cyber–physical systems

Adaptive distributed monitors of spatial properties for cyber–physical systems

Cautious Adaptation of Defiant Components

mRUBiS

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