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In this section we discuss our implementation of the approach described in \mysection\ref{se:overview} in \tinyvm, a proof-of-concept virtual machine we developed as a playground to exercise our OSR techniques. TinyVM is based on LLVM's MCJIT compiler and supports interactive invocation of LLVM IR functions either generated at run-time or loaded from disk. The main design goal behind TinyVM is the creation of an interactive environment for IR manipulation and JIT-compilation of functions: for instance, it allows the user to insert OSR points in loaded functions, run optimization passes on them or display their CFGs, repeatedly invoke a function for a specified amount of times and so on. TinyVM supports dynamic library loading and linking, and comes with a helper component for MCJIT that simplifies tasks such as handling multiple IR modules, symbol resolution in presence of multiple versions of a function, and tracking native code and other machine-level generated object such as Stackmaps.  \subsection{Example}  To explain how \tinyvm\ implements in IR LLVM  the OSR approach of \mysection\ref{se:overview}, we consider the simple example of \myfigure\ref{fi:isord-example}. Function {\tt isord} checks whether an array of numbers is sorted according to some ordering specified by a comparator. The scenario we explore is profile-driven optimization, where we dynamically divert control to a faster version if the number of iterations exceeds a certain threshold. \paragraph{OSR Instrumentation.}  We use deferred compilation by instrumenting {\tt isord} in \tinyvm\ with an open OSR at the beginning of the loop body, as shown in \myfigure\ref{fig:isordfrom}. Portions added to the original code by OSR istrumentation are highlighted in grey.