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

Using ontologies for modeling context-aware services platforms

This paper discusses the suitability of using ontologies for modeling context-aware services platforms. It addresses the directions of research we are following in the WASP (Web Architectures for Services Platforms) project. For this purpose a simple scenario is considered

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

Towards a pivotal-based approach for business process alignment.

This article focuses on business process engineering, especially on alignment between business analysis and implementation. Through a business process management approach, different transformations interfere with process models in order to make them executable. To keep the consistency of process model from business model to IT model, we propose a pivotal metamodel-centric methodology. It aims at keeping or giving all requisite structural and semantic data needed to perform such transformations without loss of information. Through this we can ensure the alignment between business and IT. This article describes the concept of pivotal metamodel and proposes a methodology using such an approach. In addition, we present an example and the resulting benefits

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

A Framework for Agile Development of Component-Based Applications

Agile development processes and component-based software architectures are two software engineering approaches that contribute to enable the rapid building and evolution of applications. Nevertheless, few approaches have proposed a framework to combine agile and component-based development, allowing an application to be tested throughout the entire development cycle. To address this problematic, we have built CALICO, a model-based framework that allows applications to be safely developed in an iterative and incremental manner. The CALICO approach relies on the synchronization of a model view, which specifies the application properties, and a runtime view, which contains the application in its execution context. Tests on the application specifications that require values only known at runtime, are automatically integrated by CALICO into the running application, and the captured needed values are reified at execution time to resume the tests and inform the architect of potential problems. Any modification at the model level that does not introduce new errors is automatically propagated to the running system, allowing the safe evolution of the application. In this paper, we illustrate the CALICO development process with a concrete example and provide information on the current implementation of our framework

Dynamic Model-based Management of Service-Oriented Infrastructure.

Models are an effective tool for systems and software design. They allow software architects to abstract from the non-relevant details. Those qualities are also useful for the technical management of networks, systems and software, such as those that compose service oriented architectures. Models can provide a set of well-defined abstractions over the distributed heterogeneous service infrastructure that enable its automated management. We propose to use the managed system as a source of dynamically generated runtime models, and decompose management processes into a composition of model transformations. We have created an autonomic service deployment and configuration architecture that obtains, analyzes, and transforms system models to apply the required actions, while being oblivious to the low-level details. An instrumentation layer automatically builds these models and interprets the planned management actions to the system. We illustrate these concepts with a distributed service update operation

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

Enrichment of raw sensor data to enable high-level queries

Sensor networks are increasingly used across various application domains. Their usage has the advantage of automated, often continuous, monitoring of activities and events. Ubiquitous sensor networks detect location of people and objects and their movement. In our research, we employ a ubiquitous sensor network to track the movement of players in a tennis match. By doing so, our goal is to create a detailed analysis of how the match progressed, recording points scored, games and sets, and in doing so, greatly reduce the eort of coaches and players who are required to study matches afterwards. The sensor network is highly efficient as it eliminates the need for manual recording of the match. However, it generates raw data that is unusable by domain experts as it contains no frame of reference or context and cannot be analyzed or queried. In this work, we present the UbiQuSE system of data transformers which bridges the gap between raw sensor data and the high-level requirements of domain specialists such as the tennis coach