Fuzz Testing Is the Best Thing to Happen to Our Application Tests

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • tsbs

    Time Series Benchmark Suite, a tool for comparing and evaluating databases for time series data

  • 1. correctness: from small units tests to relatively complex integrations tests. they typically populate a test database and query it via various interfaces, such as REST or the Postgres protocol. we use Azure Pipelines to execute them - testing in MacoOS, Linux (both Intel and ARM) and Windows.

    2. performance: we tend to use the TSBS project for most of our performance testing and profiling. fun fact: we actually had to patch it as the vanilla TSBS was a bottleneck in some tests. Sadly, the PR with the improvements is still not merged: https://github.com/timescale/tsbs/pull/186

  • oss-fuzz

    OSS-Fuzz - continuous fuzzing for open source software.

  • 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/

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    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • syzkaller

    syzkaller is an unsupervised coverage-guided kernel fuzzer

  • The key to modern fuzzing is feedback, usually some kind of coverage testing of the program under test. This allows the fuzzer to be much smarter about how it finds new code paths, and makes fuzzing find bugs a lot quicker.

    Google have a project to do fuzzing on Linux system calls using coverage feedback: https://github.com/google/syzkaller

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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