| Summary: | Driven by the need of a very demanding world, new technology arises as a way to solve problems found in practice. In the context of software, this occurs in the form of new programming paradigms, new application design methodologies, new tool support and new architectural patterns. Newly developed systems can take advantage of recent advances and choose from a state-of-the-art portfolio of techniques, taking stock of an understanding built across the years, learning from past, good and bad, experiences. However, existing software was built in a completely different context. Software engineering advances occur at a very fast pace, and applications are quickly seen as legacy due to a number of reasons, including difficulties to adapt to business needs, lack of integration capabilities with other systems, or general maintenance issues. There are various approaches to address these problems depending on the requirements or major concerns. The solution can either be rewriting the applications from scratch or evolving the existing systems. This thesis presents a methodology for systematically addressing the evolution of existing application into more modern architectures, including proposing implementations to address several classes of modernisation, with particular emphasis in reengineering towards tiered architectures and service-oriented architectures. The methodology is based on a combination of source code pattern detection guiding the extraction of structural graph models, rule-based transformations of these models, and the generation and execution of code-level refactoring scripts to affect the actual changes to the software. This dissertation presents the process, methodology, and tool support. Additionally, the proposed techniques are evaluated in the context of case studies, in order to allow conclusions regarding applicability, scalability, and overall benefits, both in terms of computational and human effort.
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