Summary:
JSC's utf16 -> utf8 conversion crashes on encountering bad utf16. Instead, use our own conversion (conveniently copied from fbjni).
Original fix thanks to rigdern (https://github.com/facebook/react-native/pull/9302)
Reviewed By: mhorowitz
Differential Revision: D3746947
fbshipit-source-id: 29887ca720f6a2b074f01f853bad28a083b273bc
Summary:
We have a lot of small-ish calls to JSC and within the bridge that add up during TTI. This gives us a way to measure them in aggregate in a reasonable way.
From the comments:
MicroProfiler is a performance profiler for measuring the cumulative impact of
a large number of small-ish calls. This is normally a problem for standard profilers
like Systrace because the overhead of the profiler itself skews the timings you
are able to collect. This is especially a problem when doing nested calls to
profiled functions, as the parent calls will contain the overhead of their profiling
plus the overhead of all their childrens' profiling.
MicroProfiler attempts to be low overhead by 1) aggregating timings in memory and
2) trying to remove estimated profiling overhead from the returned timings.
To remove estimated overhead, at the beginning of each trace we calculate the
average cost of profiling a no-op code section, as well as invoking the average
cost of invoking the system clock. The former is subtracted out for each child
profiler section that is invoked within a parent profiler section. The latter is
subtracted from each section, child or not.
The usage is similar to Systrace: you put a MICRO_PROFILER_BLOCK in the block you want to profile and C++ RAII will handle timing it.
After MicroProfiler::stopProfiling() is called, a table of tracing data is emitted
to glog (which shows up in logcat on Android).
Differential Revision: D3635319
fbshipit-source-id: 01390b8ac76a68dd425cba2adfdde6e4957440cc
Emil Sjolander
Hoa Dinh
Pieter De Baets
Chris Hopman
Adam Ernst
Marc Horowitz
Andy Street
Lukas Piatkowski
Michał Gregorczyk
David Aurelio
Greg Pstrucha
Mark Wang