No abstract

No abstract

Software Development is a complex process, in which every software product is a knowledge representation of all the involved people. In agile software development, knowledge is prone to vaporise, because documentation is not a priority as indicated in the agile manifesto. This condition generates problems such as poor understanding of the requirements, knowledge transfer deficiency among developers, time wasted by developers while searching for knowledge. The objective of this work is to reduce architectural knowledge vaporisation by means of knowledge condensation to support expertise location (high-level knowledge at a given time). This through an ontology that will condensate the knowledge in the code phase. This study presents the description of an ontology development process following the Methontology Framework. Results show that the proposed ontology does not present incongruence or inconsistency and answers the competency questions correctly. The main contribution of this study is the ontology which brings several benefits such as a shared concept of the knowledge in the code phase and a way to link the artefacts (resources used by developers in the project) and the experts (artefacts provider).

No abstract

Software product line (SPL) engineering has proven to improve software quality and shorten development cycles, cost and time. In product line engineering, product derivation is concerned with the realization of the variability at the implementation level. However, the majority of research works focuses on instantiating the variants selected in the final product, while the derivation at the architecture level has been poorly explored. As product line engineers often customize the product architecture by hand during the application engineering phase, the derivation and customization processes of the product line architecture might be in some cases error-prone. Consequently, in this research we present an Ontology-based product Architecture Derivation (OntoAD) framework which automates the derivation of product-specific architectures from an SPL architecture. Our solution uses a language-independent model to specify the product line architecture (PLA) and a model-driven engineering approach for architecture derivation activities. We use an ontology formalism to reason about the automatic generation of model-to-model transformation rules based on the selection of features and we illustrate our approach using a voice over IP motivating example. Finally, we report results about scalability and performance regarding the number of architectural variants and constraints.