10,551 research outputs found
Model-driven performance evaluation for service engineering
Service engineering and service-oriented architecture as an
integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of
measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised
for the empirical performance evaluation of model-driven developed service systems
Semantic model-driven development of web service architectures.
Building service-based architectures has become a major area of interest since the advent of Web services. Modelling these architectures is a central activity. Model-driven development is a recent approach to developing software systems based on the idea of making models the central artefacts for design representation, analysis, and code generation.
We propose an ontology-based engineering methodology for semantic model-driven composition and transformation of Web service architectures. Ontology technology as a logic-based knowledge representation and reasoning framework can provide answers to the needs of sharable and reusable semantic models and descriptions needed for service engineering. Based on modelling, composition and code generation techniques for service architectures, our approach provides a methodological framework for ontology-based semantic service architecture
Quality-aware model-driven service engineering
Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects
ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box
character of services
Automated Mapping of UML Activity Diagrams to Formal Specifications for Supporting Containment Checking
Business analysts and domain experts are often sketching the behaviors of a
software system using high-level models that are technology- and
platform-independent. The developers will refine and enrich these high-level
models with technical details. As a consequence, the refined models can deviate
from the original models over time, especially when the two kinds of models
evolve independently. In this context, we focus on behavior models; that is, we
aim to ensure that the refined, low-level behavior models conform to the
corresponding high-level behavior models. Based on existing formal verification
techniques, we propose containment checking as a means to assess whether the
system's behaviors described by the low-level models satisfy what has been
specified in the high-level counterparts. One of the major obstacles is how to
lessen the burden of creating formal specifications of the behavior models as
well as consistency constraints, which is a tedious and error-prone task when
done manually. Our approach presented in this paper aims at alleviating the
aforementioned challenges by considering the behavior models as verification
inputs and devising automated mappings of behavior models onto formal
properties and descriptions that can be directly used by model checkers. We
discuss various challenges in our approach and show the applicability of our
approach in illustrative scenarios.Comment: In Proceedings FESCA 2014, arXiv:1404.043
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