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El autor Jose Angel Taboada ha publicado 4 artículo(s):

2 - Semantic mediation of observation datasets through Sensor Observation Services

This paper describes a first effort for the semantic mediation between heterogeneous environmental observation datasets through the Sensor Observation Service (SOS) standard proposed by the Open Geospatial Consortium. The solution enables application domain experts to provide an ontology with semantic data integration knowledge, which is next combined with data source knowledge during the evaluation of global SOS GetObservation requests. This enables the development of a more general purpose solution that may be adapted to different application domains by just changing the ontology. Besides, users without specific application domain skills and knowledge may now develop new semantically enabled applications.Finally, the design of the framework is based on the well-known Mediator/Wrapper architecture and follows a Local As View data integration approach, which simplifies the incorporation of new datasets without having to change the existing data integration knowledge.

Autores: Manuel A. Regueiro / José R.R. Viqueira / Christoph Stasch / Jose Angel Taboada / 
Palabras Clave: Environmental data - Observation data - Semantic mediation - Semantic Web - Sensor data - Web service

3 - Software Design Smell Detection: a systematic mapping study

Design Smells are indicators of situations that negatively affect software quality attributes such as understandability, testability, extensibility, reusability, and maintainability in general. Improving maintainability is one of the cornerstones of making software evolution easier. Hence, Design Smell Detection is important in helping developers when making decisions that can improve software evolution processes. After a long period of research, it is important toorganize the knowledge produced so far and to identify current challenges and future trends. In this paper, we analyze 18 years of research into Design Smell Detection. There is a wide variety of terms that have been used in the literature to describe concepts which are similar to what we have defined as «Design Smells», such as design defect, design flaw, anomaly, pitfall, antipattern, and disharmony. The aim of this paper is to analyze all these terms and include them in the study. We have used the standard systematic literature review method based on a comprehensive set of 395 articles published in different proceedings, journals, and book chapters. We present the results in different dimensions of Design Smell Detection, such as the type or scope of smell, detection approaches, tools, applied techniques, validation evidence, type of artifact in which the smell is detected, resources used in evaluation, supported languages, and relation between detected smells and software quality attributes according to a quality model. The main contributions of this paper are, on the one hand, the application of domain modeling techniques to obtain a conceptual model that allows the organization of the knowledge on Design Smell Detection and a collaborative web application built on that knowledge and, on the other, finding how tendencies have moved across different kinds of smell detection, as well as different approaches and techniques. Key findings for future trendsinclude the fact that all automatic detection tools described in the literature identify Design Smells as a binary decision (having the smell or not), which is an opportunity to evolve to fuzzy and prioritized decisions. We also find that there is a lack of human experts and benchmark validation processes, as well as demonstrating that Design Smell Detection positively influences quality attributes.

Autores: Khalid Alkharabsheh / Yania Crespo / M. Esperanza Manso / Jose Angel Taboada / 
Palabras Clave: Antipatterns - Design Smell - Detection tools - Quality models - Systematic Mapping Study

4 - Factores que tienen en cuenta los desarrolladores en la priorización de smells para su corrección: conclusiones después de una réplica.

La presencia de design smells es uno de los factores que contribuye a aumentar la deuda técnica, es por ello su gestión cobra cada vez más importancia. En este documento se presenta la réplica de un estudio en el que, 10 desarrolladores examinaron issues relacionados con bad smells detectados en un proyecto software con el que no estaban familiarizados, ordenando los que deben modificarse primero, y proporcionando las razones por las que priorizaron así los issues causados por smells. Estas razones sirvieron de base para elaborar un ranking de 13 factores por los que los desarrolladores se guiaron para priorizar la reparación de las clases smells. Este conjunto de 13 factores es el mismo con el que se ha trabajado en esta réplica, con el fin de estudiar si la ordenación de los 13 factores es similar a la obtenida en el estudio original.En esta réplica se incluyen sujetos (35) que sí están familiarizados con los proyectos que examinarán (15) para priorizar las clases con smells. En este caso se considerará solamente el smell God Class. Los resultados de la réplica, cuando se compararon las dos ordenaciones de factores, no son concluyentes, pero sí se ha observado que los dos primeros factores coinciden: «Importancia del Módulo» y «Relevancia de la tarea», y también coinciden los últimos. De esto se puede concluir que toda técnica de priorización de clases detectadas con smell debe tener en cuenta esos dos factores considerados los mas importantes por ambos grupos. Por tanto, las herramientas de soporte a la priorización deben ser capaces de capturar esta información. Otra conclusión obtenida es que el grado de familiaridad de los desarrolladores con los proyectos puede influir en la priorización, y que ésta puede depender del tipo de smell.

Autores: Khalid Alkharabsheh / Yania Crespo / M. Esperanza Manso / Jose Angel Taboada / 
Palabras Clave: Correlación de Spearman - Factores en la Priorización - Priorización de smells - Réplica - Test de Kendall