This is a template for a simple project for learning some of the LLVM APIs relevant for dynamic analysis. It involves instrumenting an LLVM module in order to produce a new program that collects frequency information for edges in the call graph.

Building with CMake

1. Clone the template repository.

    git clone https://github.com/nsumner/callgraph-profiler-template.git
   

2. Create a new directory for building.

    mkdir cgbuild
   

3. Change into the new directory.

    cd cgbuild
   

4. Run CMake with the path to the LLVM source.

    cmake -DCMAKE_EXPORT_COMPILE_COMMANDS=True \
        -DLLVM_DIR=</path/to/LLVM/build>/lib/cmake/llvm/ ../callgraph-profiler-template
   

5. Run make inside the build directory:

    make
   

When you have successfully completed the project, this will produce a tool for profiling the callgraph called bin/callgraph-profiler along with supporting libraries in lib/.

Note, building with a tool like ninja can be done by adding -G Ninja to the cmake invocation and running ninja instead of make.

Running

First suppose that you have a program compiled to bitcode:

clang -g -c -emit-llvm ../callgraph-profiler-template/test/test.c -o calls.bc

Running the call graph profiler:

bin/callgraph-profiler calls.bc -o calls
./calls

When you have successfully completed the exercise, running an instrumented program like ./calls in the above example should produce a file called profile-results.csv in the current directory. The file should be formatted as follows:

<caller function name>, <call site file name>, <call site line #>, <callee function name>, <(call site,callee) frequency>