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A previous study by Lameed and Hendren~\cite{lameed2013feval} shows that the overhead of an \feval\ call is significantly higher than a direct call, especially in JIT-based execution environments such as McVM~\cite{chevalier2010mcvm} and the proprietary MATLAB JIT accelerator by Mathworks. In fact, the presence of an \feval\ instruction can disrupt the results of intra- and inter-procedural level for type and array shape inference analyses, which are key factors for efficient code generation.  Lameed and Hendren thus propose and implement in McVM two dynamic techniques for optimizing \feval\ instructions. instructions:  \begin{itemize}  \item {OSR-based specialization:} when a loop containing an feval becomes hot, an OSR is fired.  \end{itemize}  \ifdefined\fullver  The first one is based on OSR: using the McOSR library~\cite{lameed2013modular}, \feval\ calls inside loops are instrumented with an OSR point and profiling code to cache the last-known types for the arguments of each \feval\ instruction. When an OSR is fired at run-time, a code generator modifies the original function by inserting a guard to choose between a fast path containing a direct call and a slow path with the original \feval\ call. The second technique is less general and uses value-based JIT compilation: when the first argument of an \feval\ call is an argument of the enclosing function, the compiler replaces each call to this function in all of its callers with a call to a special dispatcher. At run-time, the dispatcher evaluates the value of the argument to use for the \feval\ and executes either a previously compiled cached code or generates and JIT-compiles a version of the function optimized for the current value.