deletions | additions       diff --git a/eval-new-approach.tex b/eval-new-approach.tex  index 7f0885a..e49d188 100644  --- a/eval-new-approach.tex  +++ b/eval-new-approach.tex 
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\subsection{A New Approach}  \label{ss:eval-opt-mcvm}  In this section, we present a new approach that combines the flexibility of OSR-based specialization with the efficiency of the JIT-based method, answering an open question raised by Lameed and Hendren~\cite{lameed2013feval}. The key idea is to lift the $f$-to-$f'$ optimization performed by the OSR-based specialization from IR to IIR level. This makes it possible to perform type inference in $f'$, generating a much more efficient code. The main technical challenge of this idea is that the program's  state in $f$ at the OSR point may be incompatible with the state of $f'$ from which execution continues. Indeed, some variables may be boxed in $f$ and unboxed in $f'$. Hence, compensation code is needed to adjust the state by performing live variable unboxing during the OSR. %The main idea for optimizing a function $f$ containing an \feval\ instruction is to dynamically generate a variant $f'$ where the \feval$(g,...)$ is replaced by a direct call of the form $g(...)$. The key to efficiency is the ability to perform type inference on the IIR level, [...] 
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\noindent We remark that our implementation heavily depends on \osrkit's ability to handle compensation code.   \paragraph{Analysis Pass.} In the analysis pass is fully integrated in McVM's analysis manager. We group \feval\ instructions whose first argument is reached by the same definition, and for each group we mark for instrumentation only those instructions not dominated by others, so that the function can be optimized as early as possible at run-time.   \ifdefined \fullver  \paragraph{Analysis Pass.}  The analysis pass pass, which is fully integrated in McVM's analysis manager, groups \feval\ instructions whose first argument is reached by the same definition, and for each group marks for instrumentation only those instructions not dominated by others, so that the function can be optimized as early as possible at run-time.   \ifdefined \fullver  It  is also able to determine whether the value of the argument can change across two executions of the same \feval\ instruction, thus discriminating when a run-time guard must be inserted during the run-time optimization phase. \else  The analysis pass It  also determines whether the value of the argument can change across two executions of the same \feval, and a run-time guard must thus be inserted during the optimization phase. \fi  \paragraph{IIR Compiler Extension.}  When The extension operates when  the IIR compiler processes an annotated \feval\ instruction, it keeps track of the current instruction. It builds a  {\em variable map} between IIR and IR objects, and keeps track of  the {\tt llvm::BasicBlock*} $b$  created for the \feval, \feval\ in the IR code  and of  the {\tt llvm::Value*} object $g$  used as its first argument. \paragraph{OSR Inserter.}  The OSR inserter uses the $b$ and $g$ objects collected by the compiler extension as basic block and {\tt val} argument in the open-OSR stub that invokes the \feval\ optimizer, respectively.  \fi  %The  last two elements are then used by the inserter component as basic block and {\tt val} argument in the open-OSR stub that invokes the optimizer component. \newcommand{\gBase}{$f$}  \newcommand{\gOpt}{$f_{opt}$}