Littérature scientifique sur le sujet « Software architecture reconstruction »

Arquitetura de software desempenha um importante papel no desenvolvimento de software, quando explicitamente documentada, ela melhora o entendimento sobre o sistema implementado e torna possível entender a forma com que requisitos não funcionais são tratados. Apesar da relevância da arquitetura de software, muitos sistemas não possuem uma arquitetura documentada, e nos casos em que a arquitetura existe, ela pode estar desatualizada por causa da evolução descontrolada do software. O processo de recuperação de arquitetura de um sistema depende principalmente do conhecimento que as pessoas envolvidas com o software tem. Isso acontece porque a recuperação de arquitetura é uma tarefa que demanda muita investigação manual do código fonte. Pesquisas sobre recuperação de arquitetura objetivam auxiliar esse processo. A maioria dos métodos de recuperação existentes são baseados em dependência entre elementos da arquitetura, padrões arquiteturais ou similaridade semântica do código fonte. Embora as abordagem atuais ajudem na identi cação de módulos arquiteturais, os resultados devem ser melhorados de forma signi cativa para serem considerados con áveis. Então, nesta dissertação, objetivamos melhorar o suporte a recuperação de arquitetura explorando diferentes fontes de informação e técnicas de aprendizado de máquina. Nosso trabalho consiste de uma análise, considerando cinco estudo de casos, da utilidade de usar um conjunto de características de código (features, no contexto de aprendizado de máquina) para agrupar elementos em módulos da arquitetura. Atualmente não são conhecidas as características que afetam a identificação de papéis na arquitetura de software. Por isso, nós avaliamos a relação entre diferentes conjuntos de características e a acurácia obtida por um algoritmo não supervisionado na identificação de módulos da arquitetura. Consequentemente, nós entendemos quais dessas características revelam informação sobre a organização de papéis do código fonte. Nossa abordagem usando características de elementos de software atingiu uma acurácia média significativa. Indicando a relevância das informações selecionadas para recuperar a arquitetura. Além disso, nós desenvolvemos uma ferramenta para auxílio ao processo de recuperação de arquitetura de software. Nossa ferramenta tem como principais funções a avaliação da recuperação de arquitetura e apresentação de diferentes visualizações arquiteturais. Para isso, apresentamos comparações entre a arquitetura concreta e a arquitetura sugerida.<br>Software architecture plays an important role in the software development, and when explicitly documented, it allows understanding an implemented system and reasoning about how non-functional requirements are addressed. In spite of that, many developed systems lack proper architecture documentation, and if it exists, it may be outdated due to software evolution. The process of recovering the architecture of a system depends mainly on developers' knowledge requiring a manual inspection of the source code. Research on architecture recovery provides support to this process. Most of the existing approaches are based on architectural elements dependency, architectural patterns or source code semantics, but even though they help identifying architectural modules, the obtained results must be signi cantly improved to be considered reliable. We thus aim to support this task by the exploitation of di erent code-oriented information and machine learning techniques. Our work consists of an analysis, involving ve case studies, of the usefulness of adopting a set of code-level characteristics (or features, in the machine learning terminology) to group elements into architectural modules. The characteristics mainly source code metrics that a ect the identi cation of what role software elements play in software architecture are unknown. Then, we evaluate the relationship between di erent sets of characteristics and the accuracy achieved by an unsupervised algorithm the Expectation Maximization in identifying architectural modules. Consequently, we are able to understand which of those characteristics reveal information about the source code structure. By the use of code-oriented information, our approach achieves a signi cant average accuracy, which indicates the importance of the selected information to recover software architecture. Additionally, we provide a tool to support research on architecture recovery providing software architecture measurements and visualizations. It presents comparisons between predicted architectures and concrete architectures.

Tout au long de son cycle de vie, un logiciel peut connaître de nombreux changements affectant potentiellement sa conformité avec sa documentation originelle. De plus, bien qu'une documentation à jour, conservant les décisions de conception prises pendant le cycle de développement, soit reconnue comme une aide importante pour maîtriser les évolutions, la documentation des logiciels est souvent obsolète. Les modèles d’architectures sont l’une des pièces majeures de la documentation. Assurer leur cohérence avec les autres modèles d’un logiciel (incluant son code) pendant les processus d’évolution (co-évolution) est un atout majeur pour la qualité logicielle. En effet, la compréhension des architectures logicielles est hautement valorisable en termes de capacités de réutilisation, d'évolution et de maintenance. Pourtant les modèles d’architectures sont rarement explicitement disponibles et de nombreux travaux de recherche visent à les retrouver à partir du code source. Cependant, la plupart des approches existantes n'effectuent pas un strict processus de rétro-documentation afin de re-documenter les architectures "comme elles sont implémentées" mais appliquent des étapes de ré-ingénierie en regroupant des éléments de code dans de nouveaux composants. Ainsi, cette thèse propose un processus de re-documentation des architectures telles qu’elles ont été conçues et implémentées, afin de fournir un support d’analyse des décisions architecturales effectives. Cette re-documentation se fait par l’analyse du code orienté objet et les descripteurs de déploiement de projets. Le processus re-documente les projets dans le langage de description d’architecture Dedal, qui est spécialement conçu pour contrôler et guider l’évolution des logiciels.Un autre aspect très important de la documentation des logiciels est le suivi de leurs différentes versions. Dans de nombreuses approches et gestionnaires de version actuels, comme Github, les fichiers sont versionnés de manière agnostique. S’il est possible de garder une trace de l’historique des versions de n’importe quel fichier, aucune information ne peut être fournie sur la sémantique des changements réalisés. En particulier, lors du versionnement d’éléments logiciels, il n’est fourni aucun diagnostic de retro-compatibilité avec les versions précédentes. Cette thèse propose donc un mécanisme de versionnement d’architectures logicielles basé sur le métamodèle et les propriétés formelles de l’ADL Dedal.Il permet d’analyser automatiquement les versions en termes de substituabilité, de gérer la propagation de version et d’incrémenter automatiquement les numéros de versions en tenant compte de l’impact des changements. En proposant cette approche formelle, cette thèse vise à prévenir le manque de contrôle des décisions architecturale (dérive / érosion).Cette thèse s’appuie sur une étude empirique appliquant les processus de re-documentation et de versionnement à de nombreuses versions d’un projet industriel extrait de GitHub<br>All along its life-cycle, a software may be subject to numerous changes that may affect its coherence with its original documentation. Moreover, despite the general agreement that up-to-date documentation is a great help to record design decisions all along the software life-cycle, software documentation is often outdated. Architecture models are one of the major documentation pieces. Ensuring coherence between them and other models of the software (including code) during software evolution (co-evolution) is a strong asset to software quality. Additionally, understanding a software architecture is highly valuable in terms of reuse, evolution and maintenance capabilities. For that reason, re-documenting software becomes essential for easing the understanding of software architectures. However architectures are rarely available and many research works aim at automatically recovering software architectures from code. Yet, most of the existing re-documenting approaches do not perform a strict reverse-documenting process to re-document architectures "as they are implemented" and perform re-engineering by clustering code into new components. Thus, this thesis proposes a framework for re-documentating architectures as they have been designed and implemented to provide a support for analyzing architectural decisions. This re-documentation is performed from the analysis of both object-oriented code and project deployment descriptors. The re-documentation process targets the Dedal architecture language which is especially tailored for managing and driving software evolution.Another highly important aspect of software documentation relates to the way concepts are versioned. Indeed, in many approaches and actual version control systems such as Github, files are versioned in an agnostic manner. This way of versioning keeps track of any file history. However, no information can be provided on the nature of the new version, and especially regarding software backward-compatibility with previous versions. This thesis thus proposes a formal way to version software architectures, based on the use of the Dedal architecture description language which provides a set of formal properties. It enables to automatically analyze versions in terms of substitutability, version propagation and proposes an automatic way for incrementing version tags so that their semantics corrrespond to actual evolution impact. By proposing such a formal approach, this thesis intends to prevent software drift and erosion.This thesis also proposes an empirical study based on both re-documenting and versioning processes on numerous versions on an enterprise project taken from Github

The essence of this dissertation was to explore the synergies between fashion and architecture to inform the design of a resource rich environment.<br>Dissertation (MArch(Prof))--University of Pretoria, 2009.<br>Architecture<br>unrestricted