Clang-based call-graph generation tool for MetaCG. It has the components CGCollector, CGMerge and CGValidate to construct the partial MCG per translation unit, merge the partial MCGs into the final whole-program MCG and validate edges against a full Score-P profile, respectively.
It is easiest to apply CGCollector, when a compilation database (compile_commands.json) is present.
Then, CGCollector can be applied to a single source file using
$> cgc target.cpp
cgc is a wrapper script that (tries to) determines the paths to the Clang standard includes.
Subsequently, the resulting partial MCGs are merged using CGMerge to create the final, whole-program call-graph of the application.
$> echo "null" > $IPCG_FILENAME
$> find ./src -name "*.mcg" -exec cgmerge $IPCG_FILENAME $IPCG_FILENAME {} +
The easiest approch to apply the CGCollector / CGMerge toolchain to a multi-file project is using the TargetCollector.py tool.
It is a convenience tool around CMake's file API that allows to configure the target project and apply the CGCollector / CGMerge to only the source files required for a given CMake target.
Check out the graph/test/integration/TargetCollector/TestRunner.sh script for an example invocation.
In case you want to apply the CGCollector / CGMerge toolchain to a non-CMake project, you need to resort to manually finding the files that need to be processed and merged for the given use case.
Optionally, you can test the call graph for missing edges, by providing an unfiltered application profile that was recorded using Score-P in the Cube library format. This is done using the CGValidate tool, which also allows to patch all missing edges and nodes.