Modeling the variability space of self-adaptive applications

Modeling self-adaptive applications is a difficult task due to the complex relationships they have with their environments. Designers of such applications strive to model accurately a few (re)-configuration possibilities deemed to be the most relevant with respect to environmental changes. This deliberate restriction of the variability space is cumbersome and may unnecessarily reject interesting (re)- configuration possibilities. We employ software product- line techniques to properly cover the whole variability space of a self-adaptive application. This variability space is partitioned across three dimensions. Functional variability is modeled through a feature diagram whose features are realized by a set of components to be deployed on a platform. Topological variability is modeled via an UML collaboration excluding irrelevant configurations. Platform variability is modeled through constraints to be satisfied by configurations. For each dimension, we exhibit properties capturing the environment. Our modeling approach is il- lustrated on a web-server example.