mirror of
https://github.com/nlohmann/json.git
synced 2024-12-12 12:09:08 +08:00
47 lines
2.4 KiB
Markdown
47 lines
2.4 KiB
Markdown
# fastcov
|
|
A massively parallel gcov wrapper for generating intermediate coverage formats *fast*
|
|
|
|
The goal of fastcov is to generate code coverage intermediate formats *as fast as possible* (ideally < 1 second), even for large projects with hundreds of gcda objects. The intermediate formats may then be consumed by a report generator such as lcov's genhtml, or a dedicated front end such as coveralls. fastcov was originally designed to be a drop-in replacement for lcov (application coverage only, not kernel coverage).
|
|
|
|
Currently the only intermediate formats supported are gcov json format and lcov info format. Adding support for other formats should require just a few lines of python to transform gcov json format to the desired shape.
|
|
|
|
In order to achieve the massive speed gains, a few constraints apply:
|
|
|
|
1. GCC version >= 9.0.0
|
|
|
|
These versions of GCOV have support for JSON intermediate format as well as streaming report data straight to stdout
|
|
|
|
2. Object files must be either be built:
|
|
|
|
- Using absolute paths for all `-I` flags passed to the compiler
|
|
- Invoking the compiler from the same root directory
|
|
|
|
If you use CMake, you are almost certainly satisfying the second constraint (unless you care about `ExternalProject` coverage).
|
|
|
|
## Sample Usage:
|
|
```bash
|
|
$ cd build_dir
|
|
$ fastcov.py --zerocounters
|
|
$ <run unit tests>
|
|
$ fastcov.py --exclude /usr/include --lcov -o report.info
|
|
$ genhtml -o code_coverage report.info
|
|
```
|
|
|
|
## Legacy fastcov
|
|
|
|
It is possible to reap most of the benefits of fastcov for GCC version < 9.0.0 and >= 7.1.0. However, there will be a *potential* header file loss of correctness.
|
|
|
|
`fastcov_legacy.py` can be used with pre GCC-9 down to GCC 7.1.0 but with a few penalties due to gcov limitations. This is because running gcov in parallel generates .gcov header reports in parallel which overwrite each other. This isn't a problem unless your header files have actual logic (i.e. header only library) that you want to measure coverage for. Use the `-F` flag to specify which gcda files should not be run in parallel in order to capture accurate header file data just for those. I don't plan on supporting `fastcov_legacy.py` aside from basic bug fixes.
|
|
|
|
## Benchmarks
|
|
|
|
Anecdotal testing on my own projects indicate that fastcov is over 100x faster than lcov and over 30x faster than gcovr:
|
|
|
|
Project Size: ~250 .gcda, ~500 .gcov generated by gcov
|
|
|
|
Time to process all gcda and parse all gcov:
|
|
|
|
- fastcov: ~700ms
|
|
- lcov: ~90s
|
|
- gcovr: ~30s
|