Aspect-Oriented Compositions for Dynamic Behavior Models

The crosscutting problem can be observed at scenario modeling levelwhere one model may present several tangled concerns, compromising requirementsand system evolution. To avoid this problem, we can deal with aspectualscenarios by modularizing and thus separating them from other scenarios. Also, itis desirable to analyze how the crosscutting scenarios interact with other scenariosat early stages of software development, otherwise these interactions will only becomeclear during later stages when problems are much more expensive to solve.But to achieve that scenario modularization is not enough, we need efficient modelcomposition mechanisms to allow the system to be analyzed and validated in itsentirety. We introduce the Modeling Aspects Using a Transformation Approach(MATA), an expressive technique based on graph transformations, where aspectualscenarios, here represented as sequence diagram and state machines, will bemodeled and composed efficiently. An example, based on a common case study,illustrates the usage of MATA’s modularization and composition mechanisms.