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\item {\em Global optimizations}: lowering OSR instrumentation code along with the application code can generate faster code than local binary instrumentation. For instance, dead code elimination can suppress from \fosrto\ portions of code that would no longer be needed when jumping to the landing pad \textsf{L'}, producing smaller code and enabling better register allocation and instruction scheduling.  \item {\em Debugging and Profiling}: preserving ABI conventions in the native code versions of \fosrfrom, \fstub, and \fosrto\ helps debuggers and profilers more precisely locate the current execution context and collect more informative data.  %avoiding low-lever tampering with stack frames can more easily preserve ABI calling conventions  \item {\em Abstraction}: the approach is amenable to a clean instrumentation API that abstracts the OSR implementation details, allowing a front-end to focus on where to insert OSR points by independently on the final target architecture.  %by  analyzing code at an intermediate representation level. \end{enumerate}  \noindent A natural question is whether encoding OSR at a higher level of abstraction can result in poorer performance than binary code approaches. We address this issue in Section~\ref{se:osr-llvm}, where we analyze the OSR machine code generated for an x86 target, and in Section~\ref{se:experiments}, where OSR performance is measured on classical benchmarks. 
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