Model-Driven Methodology for Rapid Deployment of Smart Spaces based on Resource-Oriented Architectures

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym

Extracting Knowledge from Software Artefacts to Assist Software Project Stakeholders

Software development methods should foster the exploitation of artefacts from existing code bases in order to improve software development productivity. These artefacts are commonly stored in repositories from which extracting knowledge is very difficult for several reasons, i.e., the stored data is represented in a wide variety of formats or is not usually linked properly to all the related artefacts. In this work, we address the challenge of extracting knowledge from different artefacts that can be produced within a software project. To this end, we present a Persistent Knowledge Monitor (PKM) for handling several kinds of knowledge and information related to a software project. The PKM bases on the JSON format to structure and store the different artefacts. By using a common representation format, we are able to extract knowledge more easily. Also, we provide a query language for searching and reasoning on the stored data

Extracting Knowledge from Software Artefacts to Assist Software Project Stakeholders

[EN] Software development methods should foster the exploitation of artefacts from existing code bases in order to improve software development productivity. These artefacts are commonly stored in repositories from which extracting knowledge is very difficult for several reasons, i.e., the stored data is represented in a wide variety of formats or is not usually linked properly to all the related artefacts. In this work, we address the challenge of extracting knowledge from different artefacts that can be produced within a software project. To this end, we present a Persistent Knowledge Monitor (PKM) for handling several kinds of knowledge and information related to a software project. The PKM bases on the JSON format to structure and store the different artefacts. By using a common representation format, we are able to extract knowledge more easily. Also, we provide a query language for searching and reasoning on the stored data.This work has been developed with the financial support of the European Union's Horizon 2020 research and innovation programme under grant agreement No. 824231 and the Spanish State Research Agency under the project TIN2017-84094-R and co-financed with ERDFGil Pascual, M.; Torres Bosch, MV.; Albert Albiol, M.; Pelechano Ferragud, V. (2021). Extracting Knowledge from Software Artefacts to Assist Software Project Stakeholders. Universitat Politècnica de València. 1-12. http://hdl.handle.net/10251/18147811

Quality evaluation for Model-Driven Web Engineering methodologies

Context: There are lots of approaches or methodologies in the Model-Driven Web Engineering (MDWE) context to develop Web Applications without reaching a consensus on the use of standards and scarcity of both, practical experience and tool support. Objective: Model-Driven Web Engineering (MDWE) methodologies are constantly evolving. Moreover, Quality is a very important factor to identify within a methodology as it defines processes, techniques and artifacts to develop Web Applications. For this reason, when analyzing a methodology, it is not only necessary to evaluate quality, but also to find out how to improve it. The main goal of this paper is to develop a set of Quality Characteristics and Sub-Characteristics for MDWE approaches based on ISO/ IEC standards. Method: From the software products context, some widely standards proposed, such as ISO/IEC 9126 or ISO/IEC 25000, suggest a Quality Model for software products, although up to now, there are no standard methods to assess quality on MDWE methodologies. Such methodologies can be organized into Properties, thus, a methodology has artifacts, processes and techniques. Then, each item is evaluated through a set of appropriate Quality Characteristics, depending on its nature. This paper proposes to evaluate a methodology as a product itself. Results: This paper recommends a set of Quality Characteristics and Sub-Characteristics based on these standards in order to evaluate MDWE methodologies quality. Additionally, it defines an agile way to relate these Quality Sub-Characteristics to Properties with the sole purpose of not only analyzing, but also assessing and improving MDWE methodologies. Conclusions: The application of these Quality Characteristics and Sub-Characteristics could promote efficiency in methodologies since this kind of assessment enhances both the understanding of strengths and weaknesses of approaches.Ministerio de Educación y Ciencia TIN2007-67843-C06-03Ministerio de Educación y Ciencia TIN2010-20057-C03-0

Requirements Modeling for Multi-Agent Systems

Different approaches for building modern software systems in complex and open environments have been proposed in the last few years. Some efforts try to take advantage of the agent-oriented paradigm to model/engineer complex information systems in terms of independent agents. These agents may collaborate in a computational organization (Multi-Agent Systems, MAS) by playing some specific roles having to interact with others in order to reach a global or individual goal. In addition, due to the complex nature of this type of systems, dealing with the classical functional and structural perspectives of software systems are not enough. The organizational perspective, that describes the context where these agents need to collaborate, and the social behavior perspective, that describes the different "intelligent" manners in which these agents can collaborate, need to be identified and properly specified. Several methodologies have been proposed to drive the development of MAS (e.g., Ingenias, Gaia, Tropos) although most of them mainly focus on the design and implementation phases and do not provide adequate mechanisms for capturing, defining, and specifying software requirements. Poor requirements engineering is recognized as the root of most errors in current software development projects, and as a means for improving the quality of current practices in the development of MAS, the main objective of this work is to propose a requirements modeling process to deal with software requirements covering the functional, structural, organizational, and social behavior perspectives of MAS. The requirements modeling proposed is developed within the model-driven engineering context defining the corresponding metamodel and its graphical syntax. In addition, a MAS requirements modeling process is specified using the Object Management Group's (OMG) Software Process Engineering Metamodel (SPEM). Finally, in order to illustrate the feasibility of our approach, we specified the software requirements of a strategic board game (the Diplomacy game).Rodríguez Viruel, ML. (2011). Requirements Modeling for Multi-Agent Systems. http://hdl.handle.net/10251/11416Archivo delegad

SES and Ecore for Ontology-based Scenario Modeling in Aviation Scenario Definition Language (ASDL)

The Aviation Scenario Definition Language (ASDL) is a domain-specific language proposal which aims to provide a standard aviation scenario specification mechanism and enable the reuse of scenario generation methods among different simulators. This paper presents a model-based scenario development approach that exploits Eclipse Modeling Framework (EMF) core (Ecore) and System Entity Structure (SES) for metamodeling and modeling these elements. The construction of the ASDL metamodel using both platforms is described to illustrate the processes. As a result of comparing two approaches, it is concluded that they follow a similar structure in the hierarchical definition of modeled elements despite there being different toolsets available in each method. Thereby, each metamodel can be easily converted into the other type using transformations. As an application use case, the use of the proposed ontology-based scenario development in the aviation domain is discussed, where a training tool is being developed that utilizes SES/Ecore approach to build a scenario-driven training tool for air traffic controllers

Model transformation for multi-objective architecture optimisation for dependable systems

Model-based engineering (MBE) promises a number of advantages for the development of embedded systems. Model-based engineering depends on a common model of the system, which is refined as the system is developed. The use of a common model promises a consistent and systematic analysis of dependability, correctness, timing and performance properties. These benefits are potentially available early and throughout the development life cycle. An important part of model-based engineering is the use of analysis and design languages. The Architecture Analysis and Design Language (AADL) is a new modelling language which is increasingly being used for high dependability embedded systems development. AADL is ideally suited to model-based engineering but the use of new language threatens to isolate existing tools which use different languages. This is a particular problem when these tools provide an important development or analysis function, for example system optimisation. System designers seek an optimal trade-off between high dependability and low cost. For large systems, the design space of alternatives with respect to both dependability and cost is enormous and too large to investigate manually. For this reason automation is required to produce optimal or near optimal designs.There is, however, a lack of analysis techniques and tools that can perform a dependability analysis and optimisation of AADL models. Some analysis tools are available in the literature but they are not able to accept AADL models since they use a different modelling language. A cost effective way of adding system dependability analysis and optimisation to models expressed in AADL is to exploit the capabilities of existing tools. Model transformation is a useful technique to maximise the utility of model-based engineering approaches because it provides a route for the exploitation of mature and tested tools in a new model-based engineering context. By using model transformation techniques, one can automatically translate between AADL models and other models. The advantage of this model transformation approach is that it opens a path by which AADL models may exploit existing non-AADL tools.There is little published work which gives a comprehensive description of a method for transforming AADL models. Although transformations from AADL into other models have been reported only one comprehensive description has been published, a transformation of AADL to petri net models. There is a lack of detailed guidance for the transformation of AADL models.This thesis investigates the transformation of AADL models into the HiP-HOPS modelling language, in order to provide dependability analysis and optimisation. HiP-HOPS is a mature, state of the art, dependability analysis and optimisation tool but it has its own model. A model transformation is defined from the AADL model to the HiP-HOPS model. In addition to the model-to-model transformation, it is necessary to extend the AADL modelling attributes. For cost and dependability optimisation, a new AADL property set is developed for modelling component and system variability. This solves the problem of describing, within an AADL model, the design space of alternative designs. The transformation (with transformation rules written in ATLAS Transformation Language (ATL)) has been implemented as a plug-in for the AADL model development tool OSATE (Open-source AADL Tool Environment). To illustrate the method, the plug-in is used to transform some AADL model case-studies