oss-fuzz VS rav1e

> because the ifunc code was breaking with all sorts of build options and obviously caused many problems with various sanitizers

for example, https://github.com/google/oss-fuzz/pull/10667

Have you tried Googles grpc fuzzer?

https://github.com/google/oss-fuzz/blob/master/projects/grpc...

https://www.fda.gov/medical-devices/digital-health-center-ex...

oss-fuzz: https://github.com/google/oss-fuzz :

> We support the libFuzzer, AFL++, and Honggfuzz fuzzing engines in combination with Sanitizers, as well as ClusterFuzz, a distributed fuzzer execution environment and reporting tool.

> Currently, OSS-Fuzz supports C/C++, Rust, Go, Python, Java/JVM, and JavaScript code. Other languages supported by LLVM may work too. OSS-Fuzz supports fuzzing x86_64 and i386 builds.

I love fuzzing as a technique and use it quite regularly, but running AFL++ on even a single program occupies all threads of a high end AMD server for weeks. I'm running it locally so only paying for the electricity. If it was a cloud instance it would cost a small fortune. I think this is a reason it is not used more widely.

I will note that Google have a programme for doing fuzz testing on open source projects using computer from their cloud: https://google.github.io/oss-fuzz/

Yes, mosh has fuzz tests in oss-fuzz [1].

[1] https://github.com/google/oss-fuzz/tree/master/projects/mosh

We will explore how Jazzer is used to automatically generate malicious inputs for Java programs, and how it compares to Symflower, which can automatically generate unit tests to uncover bugs and errors in your code. With the help of Jazzer, many bugs - some of them even in the OpenJDK - were found already. Also, as of March 2021, Jazzer is officially part of OSS-Fuzz, Google's cloud fuzzing engine. It should be noted that Jazzer is a pure "bug detection" utility that finds reproducers for errors in user code. Symflower can do the same, but provides additional functionalities to boost developer productivity, like generating high coverage unit tests and providing test templates for the software developer or tester.

Sure. You'll see it very often in codec implementations. From rav1e, a fast AV1 encoder mostly written in Rust: https://github.com/xiph/rav1e/tree/master/src/x86

Large portions of the algorithm have been translated into assembly for ARM and x86. Shaving even a couple percent off something like motion compensation search will add up to meaningful gains.

Or the current reference implementation of JPEG: https://github.com/libjpeg-turbo/libjpeg-turbo/tree/main/sim...

Again, if anything AOM would be the one restricting licenses to AV1 (if they chose to) except AOM has stated and also published AV1 in a way to allow license free access to development (which allows people to make forks of the official build like it's open source) and usage. (1)(2) I don't see why they would suddenly change this.

You can speed up the sampling process with --vmaf n_subsample=5, which in my experience works more accurately than either 2 or 4, possibly due to this bug/feature present in multiple encoders. You might also need to manually set the number of threads used for VMAF calculation with --vmaf n_threads=16, but YMMV.

That remember me of https://github.com/xiph/rav1e which is an AV1 encoder

I put in the request for ffmpeg passthrough mastering-display data a few years ago and haven't heard of any support yet.

It's getting there.. Initial steps for FFmepg: https://patchwork.ffmpeg.org/project/ffmpeg/list/?series=8444 rav1e: https://github.com/xiph/rav1e/pull/3000

It's entirely possible to re-use bits of other HW encoders for the first pass (motion estimation, etc).