deletions | additions       diff --git a/experim.tex b/experim.tex  index 8285cc9..f03190e 100644  --- a/experim.tex  +++ b/experim.tex 
...
\item[Q4] What kind of benefits can I expect [...]  \end{description}  \begin{itemize}  \item %\begin{itemize}  %\item  {\bf Message 1}: how much does a never-firing OSR point impact code quality? We run a program with one or more OSR points, and we measure the slowdown given by factors such as cache effects (due to code bloat), register pressure, etc. due to the presence of the OSR points. \item %\item  {\bf Message 2}: what is the overhead of an OSR transition to the same function? We run a program with a controlled OSR transition, e.g., with a counter that fires the OSR. Here we measure the impact of the actual OSR call. We compute for each benchmark: 1) the average time per OSR transition; 2) the number of transferred live variables; 3) the total benchmark time with an always-firing OSR at each iteration of the hottest loop; 4) the total benchmark time with a never-firing OSR at each iteration of the hottest loop (baseline); 5) the number of iterations of the hottest loop (equals the number of OSR transitions). \item %\item  {\bf Message 3}: what is the overhead of the library for inserting OSR points? We compute for each benchmark the time required by insertOpenOSR (OSR point insertion + stub creation) and insertFinalizedOSR (OSR point insertion + generation of continuation function). \end{itemize} %\end{itemize}  \paragraph{Impact on Code Quality.}  In order to measure how much a never-firing OSR point might impact code quality, we analyzed the source-code structure of each benchmark and profiled its run-time behavior to identify performance-critical sections for OSR point insertion. The distinction between open and resolved OSR points is nearly irrelevant in this context: we chose to focus on open OSR points, as their calls take an extra argument for profiling that we set to {\tt null}.