On the Modular Specification of NFPs: A Case Study

The modular specification of non-functional properties of systems is a current challenge of Software Engineering, for which no clear solution exists. However, in the case of Domain-Specific Languages some successful proposals are starting to emerge, combining model-driven techniques with aspect-weaving mechanisms. In this paper we show one of these approaches in practice, and present the implementation we have developed to fully support it. We apply our approach for the specification and monitoring of non-functional properties using observers to a case study, illustrating how generic observers defining non-functional properties can be defined in an independent manner. Then, correspondences between these observers and the domain-specific model of the system can be established, and then weaved into a unified system specification using ATL model transformation. Such a unified specification can also be analyzed in a natural way to obtain the required non-functional properties of the system.This work is partially funded by Research Projects TIN2011-23795 and TIN2011-15497-E

A New Approach for Quality Management in Pervasive Computing Environments

This paper provides an extension of MDA called Context-aware Quality Model Driven Architecture (CQ-MDA) which can be used for quality control in pervasive computing environments. The proposed CQ-MDA approach based on ContextualArchRQMM (Contextual ARCHitecture Quality Requirement MetaModel), being an extension to the MDA, allows for considering quality and resources-awareness while conducting the design process. The contributions of this paper are a meta-model for architecture quality control of context-aware applications and a model driven approach to separate architecture concerns from context and quality concerns and to configure reconfigurable software architectures of distributed systems. To demonstrate the utility of our approach, we use a videoconference system.Comment: 10 pages, 10 Figures, Oral Presentation in ECSA 201

GSO: Designing a Well-Founded Service Ontology to Support Dynamic Service Discovery and Composition

A pragmatic and straightforward approach to semantic service discovery is to match inputs and outputs of user requests with the input and output requirements of registered service descriptions. This approach can be extended by using pre-conditions, effects and semantic annotations (meta-data) in an attempt to increase discovery accuracy. While on one hand these additions help improve discovery accuracy, on the other hand complexity is added as service users need to add more information elements to their service requests. In this paper we present an approach that aims at facilitating the representation of service requests by service users, without loss of accuracy. We introduce a Goal-Based Service Framework (GSF) that uses the concept of goal as an abstraction to represent service requests. This paper presents the core concepts and relations of the Goal-Based Service Ontology (GSO), which is a fundamental component of the GSF, and discusses how the framework supports semantic service discovery and composition. GSO provides a set of primitives and relations between goals, tasks and services. These primitives allow a user to represent its goals, and a supporting platform to discover or compose services that fulfil them

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

Model Driven Mutation Applied to Adaptative Systems Testing

Dynamically Adaptive Systems modify their behav- ior and structure in response to changes in their surrounding environment and according to an adaptation logic. Critical sys- tems increasingly incorporate dynamic adaptation capabilities; examples include disaster relief and space exploration systems. In this paper, we focus on mutation testing of the adaptation logic. We propose a fault model for adaptation logics that classifies faults into environmental completeness and adaptation correct- ness. Since there are several adaptation logic languages relying on the same underlying concepts, the fault model is expressed independently from specific adaptation languages. Taking benefit from model-driven engineering technology, we express these common concepts in a metamodel and define the operational semantics of mutation operators at this level. Mutation is applied on model elements and model transformations are used to propagate these changes to a given adaptation policy in the chosen formalism. Preliminary results on an adaptive web server highlight the difficulty of killing mutants for adaptive systems, and thus the difficulty of generating efficient tests.Comment: IEEE International Conference on Software Testing, Verification and Validation, Mutation Analysis Workshop (Mutation 2011), Berlin : Allemagne (2011

Inference of performance annotations in web service composition models

High-quality services must keep working reliably and efficiently, and service compositions are no exception. As they integrate several internal and external services over the network, they need to be carefully designed to meet their performance requirements. Current approaches assist developers in estimating whether the selected services can fulfill those requirements. However, they do not help developers define requirements for services lacking performance constraints and historical data. Manually estimating these constraints is a time-consuming process which might underestimate or overestimate the required performance, incurring in additional costs. This work presents the first version of two algorithms which infer the missing performance constraints from a service composition model. The algorithms are designed to spread equally the load across the composition according to the probability and frequency each service is invoked, and to check the consistency of the performance constraints of each service with those of the composition