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# Spidermonkey JSAPI rooting analysis
This directory contains scripts for running Brian Hackett's static GC rooting
and thread heap write safety analyses on a JS source directory.
The easiest way to get this running is to not try to do the instrumented
compilation locally. Instead, grab the relevant files from a try server push
and analyze them locally.
Local Analysis of Downloaded Intermediate Files
1. Do a try push with "--upload-xdbs" appended to the try: ..." line.
2. Create an empty directory to run the analysis.
3. When the try job is complete, download the resulting src_body.xdb.bz2, src_comp.xdb.bz2,
and file_source.xdb.bz2 files into your directory.
4. Build an optimized JS shell with ctypes. Note that this does not need to
match the source you are analyzing in any way; in fact, you pretty much never
need to update this once you've built it. (Though I reserve the right to use
any new JS features implemented in Spidermonkey in the future...)
mkdir <objdir>
cd <objdir>
<srcpath>/js/src/configure --disable-debug --enable-optimize --enable-ctypes
make -j6 -s
5. Clone and build sixgill:
cd sixgill
./ --build
If you are on osx, the sixgill build will fail horribly. Let it, then do
make bin/ CXX=clang++
6. Make a file containing the following, with your own paths filled in:
js = "<objdir>/dist/bin/js"
sixgill_bin = "<sixgill-dir>/bin"
7a. For the rooting analysis, run
python <srcdir>/js/src/devtools/rootAnalysis/ gcTypes
7b. For the heap write analysis, run
python <srcdir>/js/src/devtools/rootAnalysis/ heapwrites
Also, you may wish to run with -v (aka --verbose) to see the exact commands
executed that you can cut & paste if needed. (I use them to run under the JS
debugger when I'm working on the analysis.)
Or if you *do* want to run the full analysis locally, then you may face the
dragons. To use it on SpiderMonkey:
1. Be on Fedora/CentOS/RedHat Linux x86_64, or a Docker image of one of those.
Specifically, the prebuilt GCC **won't work on Ubuntu**
without the `CFLAGS` and `CXXFLAGS` settings from
2. Have the Gecko build prerequisites installed.
3. Install taskcluster-vcs, eg by doing
npm install taskcluster-vcs
export PATH="$PATH:$(pwd)/node_modules/.bin"
4. In some directory, using $SRCDIR as the top of your Gecko source checkout,
run these commands:
mkdir work
cd work
( export GECKO_PATH=$SRCDIR; $GECKO_PATH/taskcluster/scripts/builder/ $(pwd) --dep )
The `--dep` is optional, and will avoid rebuilding the JS shell used to run the
analysis later.
If you see the error ``/lib/../lib64/crti.o: unrecognized relocation (0x2a) in section .init`` then have a version mismatch between the precompiled gcc used in automation and your installed glibc. The easiest way to fix this is to delete the ld provided with the precompiled gcc (it will be in two places, one given in the first part of the error message), which will cause gcc to fall back to your system ld. But you will need to additionally pass ``--no-tooltool`` to With the current package, you could do the deletion with
rm gcc/bin/ld
rm gcc/x86_64-unknown-linux-gnu/bin/ld
Output goes to `analysis/hazards.txt`. This will run the
analysis on the js/src tree only; if you wish to analyze the full browser, use
( export GECKO_PATH=$SRCDIR; $GECKO_PATH/taskcluster/scripts/builder/ --project browser $(pwd) )
After running the analysis once, you can reuse the `*.xdb` database files
generated, using modified analysis scripts, by running
`analysis/` (or pass `--list` to see ways to select even more
restrictive parts of the overall analysis; the default is `gcTypes` which will
do everything but regenerate the xdb files).
Also, you can pass `-v` to get exact command lines to cut & paste for running the
various stages, which is helpful for running under a debugger.
## Overview of what is going on here
So what does this actually do?
1. It downloads a GCC compiler and plugin ("sixgill") from Mozilla servers, using
"tooltool" (a binary archive tool).
2. It runs `run_complete`, a script that builds the target codebase with the
downloaded GCC, generating a few database files containing control flow
graphs of the full compile, along with type information etc.
3. Then it runs ``, a Python script, which runs all the scripts
which actually perform the analysis -- the tricky parts.
(Those scripts are written in JS.)