In this decade we are experiencing an ever-increasing use of embedded systems; fast prototyping, time to market and severe implementation constraints must be faced to provide an effective -low cost -solution for a given application. To this end, several algorithmic formalisms are available to describe and validate complex systems at a behavioral level in order to minimize development costs and facilitate the integration of design and implementation constraints. Unfortunately, conventional development environments for embedded systems cannot directly manipulate a soft-computing paradigm unless an algorithmic description is available. In general, such a description is the result of a training procedure, which, by following the selection of the most suitable soft-computing paradigm, configures it. The paper addresses the issues related to the integration of soft-computing paradigms within conventional development environments for embedded systems. The analysis is carried out at a behavioral abstraction level.