8,265 research outputs found
TURTLE-P: a UML profile for the formal validation of critical and distributed systems
The timed UML and RT-LOTOS environment, or TURTLE for short, extends UML class and activity diagrams with composition and temporal operators. TURTLE is a real-time UML profile with a formal semantics expressed in RT-LOTOS. Further, it is supported by a formal validation toolkit. This paper introduces TURTLE-P, an extended profile no longer restricted to the abstract modeling of distributed systems. Indeed, TURTLE-P addresses the concrete descriptions of communication architectures, including quality of service parameters (delay, jitter, etc.). This new profile enables co-design of hardware and software components with extended UML component and deployment diagrams. Properties of these diagrams can be evaluated and/or validated thanks to the formal semantics given in RT-LOTOS. The application of TURTLE-P is illustrated with a telecommunication satellite system
Model Based Development of Quality-Aware Software Services
Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration
Reliability prediction in model driven development
Evaluating the implications of an architecture design early in the software development lifecycle is important in order to reduce costs of development. Reliability is an important concern with regard to the correct delivery of software
system service. Recently, the UML Profile for Modeling Quality of Service has defined a set of UML extensions to represent dependability concerns (including reliability) and other non-functional requirements in early stages of the software
development lifecycle. Our research has shown that these extensions are not comprehensive enough to support reliability analysis for model-driven software engineering,
because the description of reliability characteristics in this profile lacks support for certain dynamic aspects that are essential in modeling reliability. In this work, we define a profile for reliability analysis by extending the UML 2.0
specification to support reliability prediction based on scenario specifications. A UML model specified using the profile is translated to a labelled transition system (LTS), which is used for automated reliability prediction and identification of implied
scenarios; the results of this analysis are then fed back to the UML model. The result is a comprehensive framework for addressing software reliability modeling, including analysis and evolution of reliability predictions. We exemplify our approach using the Boiler System used in previous work and demonstrate
how reliability analysis results can be integrated into UML models
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
A Model-Driven Approach for Business Process Management
The Business Process Management is a common mechanism recommended by a high number of standards for the management of companies and organizations. In software companies this practice is every day more accepted and companies have to assume it, if they want to be competitive. However, the effective definition of these processes and mainly their maintenance and execution are not always easy tasks. This paper presents an approach based on the Model-Driven paradigm for Business Process Management in software companies. This solution offers a suitable mechanism that was implemented successfully in different companies with a tool case named NDTQ-Framework.Ministerio de EducaciĂłn y Ciencia TIN2010-20057-C03-02Junta de AndalucĂa TIC-578
A model-driven approach to broaden the detection of software performance antipatterns at runtime
Performance antipatterns document bad design patterns that have negative
influence on system performance. In our previous work we formalized such
antipatterns as logical predicates that predicate on four views: (i) the static
view that captures the software elements (e.g. classes, components) and the
static relationships among them; (ii) the dynamic view that represents the
interaction (e.g. messages) that occurs between the software entities elements
to provide the system functionalities; (iii) the deployment view that describes
the hardware elements (e.g. processing nodes) and the mapping of the software
entities onto the hardware platform; (iv) the performance view that collects
specific performance indices. In this paper we present a lightweight
infrastructure that is able to detect performance antipatterns at runtime
through monitoring. The proposed approach precalculates such predicates and
identifies antipatterns whose static, dynamic and deployment sub-predicates are
validated by the current system configuration and brings at runtime the
verification of performance sub-predicates. The proposed infrastructure
leverages model-driven techniques to generate probes for monitoring the
performance sub-predicates and detecting antipatterns at runtime.Comment: In Proceedings FESCA 2014, arXiv:1404.043
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