el of abstraction by integrating a high-level estimation step. This results in a design loop which is tight led on high level of abstraction (called estimation loop in figure 1). For this, the evaluation of an optimization step can be done efficiently. Nevertheless, an exhaustive exploration of the design space leads to unacceptable high effort of the exploration process. This paper concentrates on algorithmic approaches on controlling the selection and application of transformations, which allows an effective exploration of the design space in an automated fashion. The paper is organized as follows: After a look at the state of the art in chapter 2, chapter 3 gives an overview on our design space exploration methodology. Chapter 4 presents some classical algorithmic search strategies adapted for transformation control, as well as our own modular approach. Chapter 5 summarizes the results of their experimental evaluation and application. 2. State of the Art In most of the approaches ...