deletions | additions       diff --git a/prev-eval-sol.tex b/prev-eval-sol.tex  index c7143b9..c16f81f 100644  --- a/prev-eval-sol.tex  +++ b/prev-eval-sol.tex 
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%\item Guard computation in $f'$ can be rather expensive, as it may require checking many parameters.  %\end{enumerate}  Our approach 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}. Similarly to OSR-based specialization, it does not place restrictions on the functions that can be optimized. On the other hand, it works at IIR (rather than IR) level as in JIT-based specialization, which makes it possible to perform type inference on the specialized code. Working at IIR level eliminates the two main sources of inefficiency of OSR-based specialization: 1) we can replace generic istructions with specialized instructions, and 2) the types of $g$'s arguments do not need to be cached or guarded as they are statically inferred. These observations are confirmed in practice by experiments on real MATLAB programs, as we will show in \mysection\ref{}. \mysection\ref{ss:experim-results}.  %Furthermore, since the dynamic code optimization works at IIR (rather than IR) level, type inference can replace generic istructions with specialized instructions. %, removing the main source of inefficiency of OSR-based specialization.