Model-Driven Productivity Evaluation for Self-Adaptive Context-Oriented Software Development

Anticipating context changes using a model-based approach requires a formal procedure for analysing and modelling their context-dependent functionality, and a 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, we 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 to select the best MDA-based methodology from the available solutions proposed in the literature. 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.