Productivity Evaluation of Self-Adaptive Software Model Driven Architecture

Anticipating context changes using a model-based approach requires a formal procedure for analysing and modelling context-dependent functionality and stable description of the architecture which supports dynamic decision-making and architecture evolution. This article demonstrates the capabilities of the context-oriented component-based application-model-driven architecture (COCA-MDA) to support the development of self-adaptive applications; the authors describe a state-of-the-art case study and evaluate the development effort involved in adopting the COCA-MDA in constructing the application. An intensive analysis of the application requirements simplified the process of modelling the application’s behavioural model; therefore, instead of modelling several variation models, the developers modelled an extra-functionality model. COCA-MDA reduces the development effort because it maintains a clear separation of concerns and employs a decomposition mechanism to produce a context-oriented component model which decouples the applications’ core functionality from the context-dependent functionality. Estimating the MDA approach’s productivity can help the software developers select the best MDA-based methodology from the available solutions. Thus, counting the source line of code is not adequate for evaluating the development effort of the MDA-based methodology. Quantifying the maintenance adjustment factor of the new, adapted, and reused code is a better estimate of the development effort of the MDA approaches.