Evaluation of UML-RT and Papyrus-RT for Modelling Self-Adaptive Systems

The iterative and incremental nature of software development using models typically makes a model of a system incomplete (i.e., partial) until a more advanced and complete stage of development is reached. Existing model execution approaches (interpretation of models or code generation) do not support the execution of partial models. Supporting the execution of partial models at early stages of software development allows early detection of defects, which can be fixed more easily and at lower cost. This paper proposes a conceptual framework for the execution of partial models, which consists of three steps: static analysis, automatic refinement, and input-driven execution. First, a static analysis that respects the execution semantics of models is applied to detect problematic elements of models that cause problems for the execution. Second, using model transformation techniques, the models are refined automatically, mainly by adding decision points where missing information can be supplied. Third, refined models are executed, and when the execution reaches the decision points, it uses inputs obtained either interactively or by a script that captures how to deal with partial elements. We created an execution engine called PMExec for the execution of partial models of UML-RT (i.e., a modeling language for the development of soft real-time systems) that embodies our proposed framework. We evaluated PMExec based on several use-cases that show that the static analysis, refinement, and application of user input can be carried out with reasonable performance, and that the overhead of approach, which is mostly due to the refinement and the increase in model complexity it causes, is manageable. We also discuss the properties of the refinement formally, and show how the refinement preserves the original behaviors of the model.

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“…The FailOver system [54], [55] is an implementation of the fail-over mechanism. It involves a set of servers processing client requests.…”

Section: Use-casesmentioning

confidence: 99%

Execution of Partial State Machine Models

Bagherzadeh

Kahani

Jahed

et al. 2022

IIEEE Trans. Software Eng.

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“…FailOver: The FailOver system [5,22] is an implementation of the fail-over mechanism. It involves a set of servers processing client requests.…”

Section: Case Studiesmentioning

confidence: 99%

A model-based architecture for interactive run-time monitoring

et al. 2020

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We present a model-based architecture for monitoring executions of models of real-time and embedded systems. This architecture is highly configurable and allows for the combination of various run-time monitoring tools, not only for observing the system execution, but also for interacting with it. Using a variety of case studies, we illustrate the use of the architecture for connecting the code generated from a model with a range of external tools for different purposes, including execution animation and run-time verification. However, the external tool can not only consume information from the execution, but also generate input for it and thus influence and steer it.

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“…The FailOver system [9,50] is an implementation of the fail-over mechanism. It involves a set of servers processing client requests.…”

Section: Use Casesmentioning

confidence: 99%

Live modeling in the context of state machine models and code generation

et al. 2020

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Live modeling has been recognized as an important technique to edit behavioral models while being executed and helps in better understanding the impact of a design choice. In the context of Model-driven Development (MDD) models can be executed by interpretation or by the translation of models into existing programming languages, often by code generation. This work is concerned with the support of live modeling in the context of state machine models when they are executed by code generation. To this end, we propose an approach that is completely independent of any live programming support offered by the target language. This independence is achieved with the help of a model transformation which equips the model with support for features which are required for live modeling. A subsequent code generation then produces a self-reflective program that allows changes to the model elements at runtime (through synchronization of design and runtime models). We have applied the approach in the context of UML-RT and created a prototype (Live-UMLRT) that provides a full set of services for live modeling of UML-RT state machines such as re-execution, adding/removing states and transitions, and adding/removing action code. We have evaluated the prototype on several use-cases. The evaluation shows that (1) generation of a self-reflective and model instrumentation can be carried out with reasonable performance, and (2) our approach can apply model changes to the running execution faster than the standard approach that depends on the live programming support of the target language.

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Evaluation of UML-RT and Papyrus-RT for Modelling Self-Adaptive Systems

Cited by 10 publications

References 17 publications

Execution of Partial State Machine Models

Execution of Partial State Machine Models

A model-based architecture for interactive run-time monitoring

Live modeling in the context of state machine models and code generation

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