Productivity on high-performance reconfigurable computers (HPRCs) is becoming a concern given the complexity of today's applications and development flows. Furthermore, the plethora of options from which application developers need to select their development environments has recently become another productivity obstacle. High-level languages (HLLs) for developing reconfigurable computing applications trade performance with ease-of-use. However, it is hard to know in a general sense how much performance one is giving up and how much ease-of-use he/she is gaining. More importantly, given the lack of standards and the uncertainty generated by sales literature, it is very hard to know the real differences that exist among different high-level programming paradigms. In order to do so, one needs a classification of HLLs programming models from a general high-performance computing (HPC) perspective. In this work, we consider a number of representative high-level tools that were selected to represent imperative programming, functional programming and graphical programming, and thereby demonstrate the applicability of our methodology. It will be shown that in spite of the disparity in concepts behind those tools, our methodology will be able to uncover the basic differences among them and assess their comparative productivity in terms of performance, and ease-of-use.