We present JOG, a framework for developing peephole optimizations and
accompanying tests for Java compilers. JOG allows developers to write
a peephole optimization as a pattern in Java itself. Such a pattern
contains code before and after the desired transformation defined by
the peephole optimization, with any necessary preconditions, and the
pattern can be written in the same way that tests for the optimization
are already written in OpenJDK. JOG automatically translates each
pattern into C/C++ code as a JIT optimization pass, and generates
tests for the optimization. Also, JOG automatically analyzes the
shadow relation between a pair of optimizations where the effect of
the shadowed optimization is overridden by the other. We used JOG to
write 162 patterns, including many patterns found in OpenJDK and LLVM,
as well as some that we proposed. We opened ten pull requests (PRs)
for OpenJDK, on introducing new optimizations, removing shadowed
optimizations, and adding generated tests for optimizations; nine of
PRs have already been integrated into the master branch of
OpenJDK. The demo video for JOG can be found at
https://youtu.be/z2q6dhOiqgw.