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Code coverage

This document describes the requirements and recommendations for enabling code coverage reports for a project using ClusterFuzz.


ClusterFuzz and code coverage

ClusterFuzz is capable of storing, presenting, and leveraging code coverage information. However, ClusterFuzz does not generate code coverage reports, as that process depends on the build system used by a project, and build systems can be very different across projects.

Setting up a code coverage builder

It is possible to set up an external builder or a Continuous Integration job that would produce code coverage data for ClusterFuzz. For C and C++ projects it is recommended to use Clang Source-based Code Coverage.

Code coverage report and stats

A typical workflow for the builder is the following:

  1. Check out the latest version of the source code for the project.
  2. Build all the fuzzers in the project with code coverage instrumentation.
  3. Download the latest corpus backup from ClusterFuzz.
  4. For every fuzzer in the project:
    • Unpack the corpus backup.
    • Run the fuzzer against the unpacked corpus.
    • Process the coverage dumps (.profraw files) using llvm-profdata merge.
    • Use the resulting .profdata file to generate $fuzzer_name.json file via llvm-cov export -summary-only.
  5. Merge all .profdata files produced by individual fuzzers into a single .profdata file using llvm-profdata merge.
  6. Use the final .profdata file to generate summary.json file for the whole project. The resulting file will include aggregate data from the all fuzzers.
  7. Use the final .profdata file to generate an HTML report using llvm-cov show -format=html. The report will include aggregate data from the all fuzzers.

As a result, the builder should produce the following artifacts:

  1. JSON files with coverage stats for every fuzzer in the project.
  2. JSON file with coverage stats for the whole project.
  3. HTML report for the whole project.

Here is an example of OSS-Fuzz code coverage job definition for Google Cloud Build. It also uses coverage_utils.py script from Chromium and this bash script.

Coverage information file

The builder needs to upload the artifacts and a JSON file containing coverage information to a GCS bucket specified in the project config (coverage.reports.bucket). The file name should be equal to the project name, e.g. zlib.json. The JSON file(s) must be uploaded to the following location:

gs://<bucket name>/latest_report_info/<project name>.json
# Example from OSS-Fuzz:
gs://oss-fuzz-coverage/latest_report_info/zlib.json

The format of the file is the following:

{
    "report_date": "YYYYMMDD",
    "fuzzer_stats_dir": "gs://path_to_directory_with_per_fuzzer_summary.json_files",
    "report_summary_path": "gs://path_to_the_project_summary.json_file",
    "html_report_url": "https://link_to_the_main_page_of_the_report",
}
  • report_date is the date when the report was generated.
  • fuzzer_stats_dir is a GCS directory containing JSON files for every fuzzer ($fuzzer_name.json).
  • report_summary_path should point to the summary.json file that includes aggregate data from the all fuzzers in the project.
  • html_report_url should point to the index.html of the HTML report.

An example of a real zlib.json file uploaded by the code coverage job on OSS-Fuzz.

{
    "report_date": "20190112",
    "fuzzer_stats_dir": "gs://oss-fuzz-coverage/zlib/fuzzer_stats/20190112",
    "report_summary_path": "gs://oss-fuzz-coverage/zlib/reports/20190112/linux/summary.json",
    "html_report_url": "https://storage.googleapis.com/oss-fuzz-coverage/zlib/reports/20190112/linux/index.html",
}