Empowering global software development with business intelligence

Context: Global Software Development (GSD) allows companies to take advantage of talent spread across the world. Most research has been focused on the development aspect. However, little if any attention has been paid to the management of GSD projects. Studies report a lack of adequate support for management’s decisions made during software development, further accentuated in GSD since information is scattered throughout multiple factories, stored in different formats and standards. Objective: This paper aims to improve GSD management by proposing a systematic method for adapting Business Intelligence techniques to software development environments. This would enhance the visibility of the development process and enable software managers to make informed decisions regarding how to proceed with GSD projects. Method: A combination of formal goal-modeling frameworks and data modeling techniques is used to elicitate the most relevant aspects to be measured by managers in GSD. The process is described in detail and applied to a real case study throughout the paper. A discussion regarding the generalisability of the method is presented afterwards. Results: The application of the approach generates an adapted BI framework tailored to software development according to the requirements posed by GSD managers. The resulting framework is capable of presenting previously inaccessible data through common and specific views and enabling data navigation according to the organization of software factories and projects in GSD. Conclusions: We can conclude that the proposed systematic approach allows us to successfully adapt Business Intelligence techniques to enhance GSD management beyond the information provided by traditional tools. The resulting framework is able to integrate and present the information in a single place, thereby enabling easy comparisons across multiple projects and factories and providing support for informed decisions in GSD management.

Identificación de impactos sobre flora rara, endémica o amenazada mediante el análisis de secuencias espaciotemporales

En el presente trabajo se muestran los resultados obtenidos a partir de una metodología de seguimiento de poblaciones de flora rara, endémica o amenazada –concretamente la cistácea Helianthemum caput-felis Boiss. en el litoral sur de la provincia de Alicante- con el fin de constatar extinciones recientes de estas especies mediante la utilización combinada de Sistemas de Información Geográfica (SIG), Sistemas de Posicionamiento Global (GPS) y la aplicación Google Earth. Finalmente se reflexiona, a partir de la experiencia de trabajo con la especie referida, sobre las ventajas que puede significar esta última aplicación a la hora de difundir los datos y facilitar así la gestión y conservación de la flora y sus hábitats.

Modelización de Sistemas Ecológicos

Presentaciones de la asignatura Modelización de Sistemas Ecológicos