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.