An Investigation on Component Based Adaptation for Feature Models

To support media applications in portable situations, it will be important for applications to know about the hidden natural conditions, furthermore to have the capacity to adjust their conduct and that of the real stage all things considered conditions change. Numerous current scattered frameworks stages backing such adjustment just in a fairly irregular way. This paper presents a principled approach to supporting adaptation through the use of reflection. More speci�cally, the paper introduces a language independent, component-based reflective architecture featuring a per-component meta-space, the use of meta-models to structure meta-space, and a consistent use of component graphs to represent composite components. The paper additionally gives an account of a nature of administration stage, giving better backing than checking and adjustment capacities. At long last, the paper clarifies a model execution of the design utilizing the article arranged programming dialect Python