Quality Evaluation of Self-Adaptive Systems

Sousa, Amanda Oliveira de; Bezerra, Carla I. M.; Andrade, Rossana M. C.; Filho, José M. S. M.

doi:10.1145/3350768.3352455

Cited by 14 publications

(14 citation statements)

References 20 publications

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“…de Sousa et al 3 show that the studies related to the performance of self-adaptive systems has been amongst the most popular ones within the academic community in the last years. They present a series of challenges for quality evaluation of self-adaptive systems regarding architecture, complexity, reference values, and tools.…”

Section: Motivation and Challengesmentioning

confidence: 99%

A procedural and flexible approach for specification, modeling, definition, and analysis for self‐adaptive systems

2021

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An adaptive system can modify its settings at runtime as a response to changes in its operational environment. To analyse this kind of systems at design time is a difficult task since it requires considering the system together with the adaptation operations, and taking into account how such adaptations act on the system. In order to use simulation-based techniques for the analysis of such systems, we not only need precise executable models of the systems to be analyzed, but also to capture the semantics of their adaptation mechanisms. Given the wide range and flexibility of adaptation operations, we need ways to allow the definition of new operations. We present a flexible approach for the definition and simulation-based analysis in design-time of adaptive component-based systems. Our approach combines an extension of the Palladio component model in e-Motions, a model of the adaptation mechanisms, and elastic requirements specification using the SYBL language. From the model of the system, its adaptation mechanisms, and its requirements, an executable Maude specification is generated for simulation. The application of the approach is illustrated on a use case that comprises some components and adaptations rules. The example is then analyzed using simulations. It is also shown that it is indeed possible to define additional metrics, specify adaptation requirements and rules which conduct simulations of the models in a more flexible way, and that the results of the simulation performed from these definitions can be used to carry on a valuable predictive performance analysis. K E Y W O R D Sadaptation specification, design-time analysis, modeling, self-adaptive behavior, self-adaptive models INTRODUCTIONSoftware architecture has become an essential element in building consistent systems as the size and complexity of software systems have increased. The necessity to take into account not only the overall structure of the system itself but also the allocation, functionality, and communication of the software components became a challenge for building

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Section: Motivation and Challengesmentioning

confidence: 99%

A procedural and flexible approach for specification, modeling, definition, and analysis for self‐adaptive systems

2021

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“…Self-Adaptive Systems (SAS) generally adapt themselves to their related changing environment [1,2,3]. Several Self-Adaptive works relied on conventional approaches dealing with the conventional whole lifecycle [2], requirements [4], design [1], modeling [1], development and evaluation [3,5]. Others works relied on nature-inspired approaches [6,7,8] based on immunity models [7,8].…”

Section: Related Workmentioning

confidence: 99%

“…Self-Adaptive Systems (SAS) have been introduced as a solution to deal with environmental changes in computer systems [1,2,3]. These systems generally adapt themselves to their related changing environment, using accurate configurations that are already available during the running time of the software.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2021

IJSEA

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The recent self-adaptive software systematic literature reviews stated clearly the following insufficiencies: (1) the need for a holistic self-adaptive software model to integrate its different aspects (2) The limitation of adaptations to context changes (3) The absence of a general and complete adaptations' picture allowing its understandability, maintainability, evaluation, reuse, and variability. (4) The need for an explicit and a detailed link with resources, and (5) a usual limitation to known events.In order to metigate these insufficiencies, this paper is proposing a holistic model that integrates the operating, adaptations, and adaptations' manager aspects. The proposed model covers all possible adaptations: operating (dealing with software functions failures), lifecycle (handling adaptations required by some software lifecycle steps), and context (facing context changes events). The presented work introduces the concept of software adaptations process integrating the specifications of all the above kind of adaptations. In fact, this work shows an explicit trace to its pure bio-inspired origin.An application of the proposed approach on a "car industry case study" demonstrated its feasibility in comparison with similar works that proved its meaningful added value and its promising research perspectives.

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“…To evaluate the output or system response of SHS via simulated experiments, it is required that the simulator reflects properly whether a chosen repair activity leads to the expected effects. System performance is reported to be one of the most common quality attributes that is measured as system response for evaluation of SHS and SAS in general [5,6]. The performance of a system can be realized via various metrics capturing the quality of the service provided by the system [18].…”

Section: Problem Space Of Shs Evaluationmentioning

confidence: 99%

“…The choice of the proper adaptation approach is a design-time decision. The quality of the design-time decisions significantly influences the overall quality attributes of SAS [5,6]. Performance and optimality are the main quality attributes meaningful for evaluation of SAS.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Self-Healing Systems: An Analysis of the State-of-the-Art and Required Improvements

Ghahremani

Giese

2020

Computers

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Evaluating the performance of self-adaptive systems is challenging due to their interactions with often highly dynamic environments. In the specific case of self-healing systems, the performance evaluations of self-healing approaches and their parameter tuning rely on the considered characteristics of failure occurrences and the resulting interactions with the self-healing actions. In this paper, we first study the state-of-the-art for evaluating the performances of self-healing systems by means of a systematic literature review. We provide a classification of different input types for such systems and analyse the limitations of each input type. A main finding is that the employed inputs are often not sophisticated regarding the considered characteristics for failure occurrences. To further study the impact of the identified limitations, we present experiments demonstrating that wrong assumptions regarding the characteristics of the failure occurrences can result in large performance prediction errors, disadvantageous design-time decisions concerning the selection of alternative self-healing approaches, and disadvantageous deployment-time decisions concerning parameter tuning. Furthermore, the experiments indicate that employing multiple alternative input characteristics can help with reducing the risk of premature disadvantageous design-time decisions.

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Quality Evaluation of Self-Adaptive Systems

Cited by 14 publications

References 20 publications

A procedural and flexible approach for specification, modeling, definition, and analysis for self‐adaptive systems

A procedural and flexible approach for specification, modeling, definition, and analysis for self‐adaptive systems

Untitled

Evaluation of Self-Healing Systems: An Analysis of the State-of-the-Art and Required Improvements

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