Reuse of software components orientated to iOS mobile devices

Within the next few pages, I will try to give a wide description of the project that I have been doing for IK4-Ikerlan. For the last six months, I have been working in developing a socket-based application for Apple devices. These devices work under the iOS operative system, which is programmed in Objective-C, a language similar to C. Although I did not have the chance to develop this application for Apple TV, I was able to create an application for iPhone and another one for iPad. The only difference between both applications was the screen resolution, but we decided to make them separately, as it would be really hard to combine both resolutions, and wallpapers, everything in the same workspace. Finally, it is necessary to add that the main goal was not to create a new application for iOS, but to translate an Android application into iOS. To achieve this, it is required to translate Java code into Objective- C, which is the language used to develop applications for all kinds of Apple devices. Fortunately, there is a tool created by Google, which helped us with this exercise. This tool is called j2ObjC, and it is still being developed.

Aprendizaje basado en proyectos aplicado a la asignatura Ingeniería del software : guía del docente y guía del estudiante

Este informe recoge las guías del docente y del estudiante para la puesta en marcha, seguimiento continuo y evaluación de la asignatura Ingeniería del Software del segundo curso del Grado en Ingeniería Informática. Todo ello basado en metodologías activas, concretamente la metodología de Aprendizaje Basado en Proyectos (ABP, o PBL de Project Based Learning). El trabajo publicado en este informe es el resultado obtenido por los autores dentro del programa de formación del profesorado en metodologías activas (ERAGIN), auspiciado por el Vicerrectorado de Calidad e Innovación Docente de la Universidad del País Vasco (UPV/EHU).

Implantar un Sistema de Gestion Integral en Software libre

El proyecto de fin de carrera “Implantar un Sistema de Gestión Integral en Software libre” se ha desarrollado en la empresa Avanzosc con sede en Azkoitia. Una peculiaridad del proyecto es que a su vez se ha utilizado como cliente otra empresa, q2K, Soluciones Informáticas en Gestión Estratégica. El objetivo del proyecto es implantar en q2K un sistema de planificación de recursos empresariales (ERP, Enterprise Resource Planning), esto le permite reunir en una única aplicación todos los procesos de negocio de la empresa. La implantación de un ERP requiere de una importante inversión ya que el coste de la licencia de un sistema ERP propietario es elevado. Una interesante alternativa para evitar este desembolso es optar por un de ERP de software libre con todas las ventajas de configuración y personalización. En nuestro caso se ha adoptado OpenERP que es un software integral, modular y adaptable, adecuado para pequeñas y medianas empresas. El desarrollo del proyecto ha estado supervisado por el equipo de trabajo de Avanzosc, empresa líder en España en implantación de OpenErp, siguiendo la metodología de trabajo propia de esta empresa.

PAnalyzer: A software tool for protein inference in shotgun proteomics

Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an easy to use multiplatform and free software tool.