\begin{abstract}
Writing an optimizing static compiler for dynamic languages is not an
easy task, since quite complex static analysis is required.
On the other hand, recent developments show that JIT compilers 
can exploit runtime type information to generate quite efficient code.
Unfortunately, writing a JIT compiler is far from being simple.
 
In this paper we report our positive experience with automatic generation
of JIT compilers as supported by the PyPy infrastructure, by
focusing  on JIT compilation for .NET.
The paper presents two main and novel contributions: we show that
partial evaluation can be used in practice for generating a JIT compiler,
and we experiment with the potentiality offered by the ability to
add a further level of JIT compilation on top of .NET.

The practicality of the approach is demonstrated by showing some
promising experiments done with benchmarks written in a simple dynamic language.
\end{abstract}

% LocalWords:  JIT PyPy