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diff --git a/benchmark/README.md b/benchmark/README.md new file mode 100644 index 00000000..e37abad2 --- /dev/null +++ b/benchmark/README.md @@ -0,0 +1,51 @@ +# American Fuzzy Lop plus plus (AFL++) + +## benchmarking + +This directory contains benchmarking tools that allow you to compare one machine +with another in terms of raw ability to execute a fuzzing target repeatedly. + +To achieve this, we use a sample program ("test-instr.c") where each path is +equally likely, supply it a single seed, and tell AFL to exit after one run of +deterministic mutations against that seed. + +Usage example: + +``` +cd aflplusplus/benchmark +python3 benchmark.py + [*] Ready, starting benchmark... + [*] Compiling the test-instr-persist-shmem fuzzing harness for the benchmark to use. + [*] singlecore test-instr-persist-shmem run 1 of 2, execs/s: 124883.62 + [*] singlecore test-instr-persist-shmem run 2 of 2, execs/s: 126704.93 + [*] Average execs/sec for this test across all runs was: 125794.28 + [*] Using 16 fuzzers for multicore fuzzing (use --fuzzers to override). + [*] multicore test-instr-persist-shmem run 1 of 2, execs/s: 1179822.66 + [*] multicore test-instr-persist-shmem run 2 of 2, execs/s: 1175584.09 + [*] Average execs/sec for this test across all runs was: 1177703.38 + [*] Results have been written to the benchmark-results.jsonl file. + [*] Results have been written to the COMPARISON file. +``` + +By default, the script will use a number of parallel fuzzers equal to your +available CPUs/threads (change with `--fuzzers`), and will perform each test +three times and average the result (change with `--runs`). + +The script will use multicore fuzzing instead of singlecore by default (change +with `--mode singlecore`) and use a persistent-mode shared memory harness for +optimal speed (change with `--target test-instr`). + +Feel free to submit the resulting line for your CPU added to the COMPARISON +file back to aflplusplus in a pull request. + +Each run writes results to [benchmark-results.jsonl](benchmark-results.jsonl) +in [JSON Lines](https://jsonlines.org/) format, ready to be pulled in to other +tools such as [jq -cs](https://jqlang.github.io/jq/) or +[pandas](https://pandas.pydata.org/) for analysis. + +## Data analysis + +There is sample data in [benchmark-results.jsonl](benchmark-results.jsonl), and +a Jupyter notebook for exploring the results and suggesting their meaning at +[benchmark.ipynb](benchmark.ipynb). + |