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strengths of both approaches". In the remaining part of this section, we extend McVM by implementing a novel optimization mechanism for \feval\ based on our OSR technique: we will show that our mechanism is as efficient as their JIT-based approach in terms of quality of generated code, and is even more general than their OSR-based approach, as it can optimize also \feval\ calls not enclosed in a loop.  \subsection{Extending McVM}  The McVM virtual machine is a complex research project developed at McGill McGill\mynote{add citation here}  and composed of several software components, including: a front-end for lowering MATLAB programs to an intermediate representation called IIR that captures all of the high-level features of the language; an interpreter for running MATLAB functions and scripts in IIR format; a manager component to perform analyses on IIR; a JIT compiler based on LLVM for generating native code for a function, thus lowering McVM IIR to LLVM IR; a set of helper components to perform fast vector and matrix operations using optimized libraries such as ATLAS, BLAS and LAPACK. %The architecture of McVM is illustrated in Figure [...] McVM implements a function versioning mechanism based on type specialization: for each IIR representation of a function, different IR versions are generated according to the types of the arguments at each call site. The number of generated versions per function is on average small (i.e., less than two), as in most cases functions are always called with the same argument types. Type specialization is the main factor for the generation of efficient code in McVM~\cite{chevalier2010mcvm}.