Resumen:
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It is widely recognised that information and communication technologies development is a risky activity. Despite the advances in software engineering, many software development projects fail to satisfy the clients' needs, ...[+]
It is widely recognised that information and communication technologies development is a risky activity. Despite the advances in software engineering, many software development projects fail to satisfy the clients' needs, to deliver on time or to stay within budget. Among the various factors that are considered to cause failure, an inadequate requirements practice stands out. Model-driven development is a relatively recent paradigm with the potential to solve some of the dragging problems of software development. Models play a paramount role in model-driven development: several modelling layers allow defining views of the system under construction at different abstraction levels, and model transformations facilitate the transition from one layer to the other. However, how to effectively integrate requirements engineering within model-driven development is still an open research challenge. This thesis integrates Communication Analysis, a communication-oriented business process modelling and requirements engineering method for information systems development, and the OO Method, an object-oriented model-driven software development method provides automatic software generation from conceptual models. We first provide a detailed specification of Communication Analysis intended to facilitate the integration; among other improvements to the method, we build an ontology-based set of concept definitions in which to ground the method, we provide precise methodological guidelines, we create a metamodel for the modelling languages included in the method, and we provide tools to support the creation of Communication Analysis requirements models. Then we perform the integration by providing a technique to systematically derive OO-Method conceptual models from Communication Analysis requirements models. The derivation technique is offered in two flavours: a set of rules to be manually applied by a human analyst, and an ATL model transformation that automates this task.
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