Abstract
The purpose of this study is to find the right model to plan and predict future evolution paths of an evolving software architecture based on past evolution data. Thus, in this paper, a model to represent the software architecture evolution process is defined. In order to collect evolution data, a simple formalism allowing to easily express software architecture evolution data is introduced. The sequential pattern extraction technique is applied to the collected evolution styles of an evolving software architecture in order to predict and plan the future evolution paths. A learning and prediction model is defined to generate the software architecture possible future evolution paths. A method for evaluating the generated paths is presented. In addition, we explain and validate our approach through a study on two examples of evolution of component-oriented software architecture.
Highlights
Software systems are becoming more complex day after day, and integrate many components.some research has focused on planning and prediction of software evolution [1,2,3,4].software architectures go hand in hand with the software products they document, they evolve together and constantly
The new approach that we introduce to express and analyze software architectures evolution styles in order to predict and plan future evolutions of theses is presented below
The objective of this study is to find the right models to respectively represent and plan the software architecture evolution process and the right methodology to predict future evolution paths of an evolving Component-Oriented software architecture based on past evolution data
Summary
Software systems are becoming more complex day after day, and integrate many components.some research has focused on planning and prediction of software evolution [1,2,3,4].software architectures go hand in hand with the software products they document, they evolve together and constantly. While a lot of works have been directed towards the problem of reusing the evolution of software architectures [5,6,7,8], it is very tedious to evolve the architecture of complex systems (distributed systems, some embedded systems, etc.). Little work has focused on the problem of planning and prediction of the future evolution of software architectures. The majority of research efforts focused on the specification, development, deployment of software architectures [9,10,11] and the analysis, design and reuse of the software architectures evolution [6,12]. Little works, to our knowledge, are devoted to planning and prediction of futures evolutions paths in software architectures
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