Traditional evaluation of user experience is subjective by nature, for what is sought is to use data from physiological and behavioral sensors to interpret the relationship that the user’s cognitive states have with the elements of a graphical interface and interaction mechanisms. This study presents the systematic review that was developed to determine the cognitive states that are being investigated in the context of Quality of Experience (QoE)/User Experience (UX) evaluation, as well as the signals and characteristics obtained, machine learning models used, evaluation architectures proposed, and the results achieved. Twenty-nine papers published in 2014–2019 were selected from eight online sources of information, of which 24% were related to the classification of cognitive states, 17% described evaluation architectures, and 41% presented correlations between different signals, cognitive states, and QoE/UX metrics, among others. The amount of identified studies was low in comparison with cognitive state research in other contexts, such as driving or other critical activities; however, this provides a starting point to analyze and interpret states such as mental workload, confusion, and mental stress from various human signals and propose more robust QoE/UX evaluation architectures.

E-learning resources are pieces of knowledge used for achieving a learning objective. One of the problems in e-training in the workplace has to do with the lack of relevance of learning resources. Here, we define a learning resource as a resource that contains information about a task or refers to a task realized within the context of an organizational process. We describe a set of activities for the generation of learning resources of objective, content, activity, and assessment types, which correspond to the pedagogical elements in learning objects. The generation goes from a documented business process using natural language processing and the learning resources produced are packaged as web services for independence and reusability purposes. Each learning resource generated is independent since it may participate in several formative sequences on its own, and it is reusable since it may be used many times without any change.

La nube computacional como modelo ubicuo, permite el suministro de servicios a clientes que acceden a ella de forma fácil y rápida. El Software como Servicio (SaaS) es uno de los modelos de mayor uso, mediante el cual las aplicaciones se despliegan y aprovisionan por los clientes vía internet mediante un navegador web en un modelo de pago por uso. Sin embargo, por su complejidad y características –reusabilidad, escalabilidad, elasticidad y personalización– el SaaS es definido por flujos de trabajo compuestos de microservicios o servicios atómicos alojados geográficamente en diferentes lugares. El SaaS en este contexto puede presentar comportamientos anormales en los resultados o fallos en la aplicación final del usuario en tiempo de ejecución. En este artículo se presenta un modelo de orquestación dinámica cuyo objetivo es disminuir las fallas o comportamientos anormales de los servicios que participan en el proceso de ejecución de las aplicaciones de negocios.

Implementing the persistence layer is a task that the Object Relational Mapping (ORMs) tools have standardized through diverse frameworks and Application Programming Interfaces (APIs). However, these ORMs and APIs have some inconveniences related to their configuration process and the time and effort it takes to learn them, amongst others. For example, every time a database is used, a configuration process is realized to map the database to obtain Plain Old Java Objects (POJOs) and Data Access Objects (DAOs). In order to overcome those disadvantages, this work contributes by proposing a reusable and extensible process that supports the automatic generation of POJOs and DAOs from database scheme metadata, through the specification of an Extended Backus–Naur Form (EBNF) grammar. A tool named GenPOJO was developed in order to test the process. Unlike the existing ORMs, the proposed process does not require the configuration steps for each database. In addition, GenPOJO does not require time to learn since the only input it receives is a file in XML (eXtensible Markup Language) format containing the database scheme metadata.

Actualmente la medición de la calidad del diseño arquitectural de software es un tópico importante para los ingenieros de software. Sin embargo, algunas métricas de calidad aún no están definidas, como lo son las métricas para medir el factor de flexibilidad y de herencia de implementación de una arquitectura de clases, enfocadas en métodos abstractos. En este trabajo de investigación se propone un conjunto de cinco métricas de calidad, tres de ellas son para medir el factor de herencia de implementación, las cuales son: Factor de Herencia de Implementación (FHI), Factor de Herencia de Implementación por Jerarquía de Clases (FHIJ) y Factor Herencia de Implementación de una Arquitectura de Clases (FHIAC); las dos restantes son para medir el factor de flexibilidad, estas son: Factor de Flexibilidad de Clase (FFC) y Factor Medio de Flexibilidad de Clases(FMFC).

Currently there are a large number of metrics to measure the quality of software architectural design, however, there are still missing metrics that are not defined in the literature, such as metrics to measure the protection of methods associated with the "Template Method" design pattern. In this work, a research applied to technological development was carried out based on the theory of measurement as a means of validation and combination of empirical conditions with formal conditions. The main result of the research was a set of four metrics that allow to evaluate the internal quality of software architectures in order to facilitate their maintenance and useful life time, as well as their reuse. Three of them measure the degree of modular protection in template methods (PMMP), variant functions (PMFV) and invariant functions (PMFI). The fourth one measures the degree of total protection that the Template Method design pattern has in a software architecture (PTTM). Finally, the metrics were implemented in a system to automate the calculation applied to three test cases where the validation was given by comparing the expected results with the obtained values. Keywords: Template Method, functional protection, variant functions, invariant functions, indirect coupling.