Most code is executed more than once. If not entire programs then
libraries remain unchanged from one run to the next. Just-in-time
compilers expend considerable effort gathering insights about code
they compiled many times, and often end up generating the same binary
over and over again. We explore how to reuse compiled code across
runs of different programs to reduce warm-up costs of dynamic
languages. We propose to use \emph{speculative contextual dispatch}
to select versions of functions from an \emph{off-line curated code
repository}. That repository is a persistent database of previously
compiled functions indexed by the context under which they were
compiled. The repository is curated to remove redundant code and to
optimize dispatch. We assess practicality by extending Ř, a
compiler for the R language, and evaluating its performance. Our
results suggest that the approach improves warmup times while
preserving peak performance.