Verify VS rr

Bogus - For creating fake data Verify - Snapshot testing for .NET MELT - For testing ILogger usage Stryker - Mutation Testing for .NET TestContainers - run docker programmatically in integration tests

Are you familiar with "snapshot testing" tools such as Verify that store expected output in files. It's still unit testing.

We can use Verify to perform snapshot testing and check for the correct output of the program. In order to make things easier and simplify working with process output capturing and invocation, I used CliWrap.

You will have to write extra code to set up a code base to get it started (there's always a large initial cost in getting things set up, and you'll be writing code that helps get the state of your application setup), but I can assure you that our team paid the initial tax and the only reason our tests change now is because of requirements changes (and maybe sometimes because the testing tools we use like Verify have some breaking changes in behavior when we upgrade). Otherwise, it helps us identify issues in our code, particularly when we do library upgrades or change to a different library. Again, our tests do not change when we completely reimplement anything, just when the external contract changes. We just get to refactor/reimplement and have confidence that the old behavior stays the same. And then you get to hook up a benchmark to your tests and, if your reason for refactoring was performance reasons, you can show that it was effective.

I assume this means you can take something like this, combine it with Snapshot/Approval testing (link to a library I have used), and then you have some quick-to-generate tests that help guard against regressions (even visual ones) by say:

I think this tool must share a lot techniques and use cases with rr. I wonder how it compares in various aspects.

https://rr-project.org/

rr "sells" as a "reversible debugger", but it obviously needs the determinism for its record and replay to work, and AFAIK it employs similar techniques regarding system call interception and serializing on a single CPU. The reversible debugger aspect is built on periodic snapshotting on top of it and replaying from those snapshots, AFAIK. They package it in a gdb compatible interface.

Hermit also lists record/replay as a motivation, although it doesn't list reversible debugging in general.

Interesting. Perhaps you can inspect the disassembly of the function in question when using Graal and HotSpot. It is likely related to that.

Another debugging technique we use for heisenbugs is to see if `rr` [1] can reproduce it. If it can then that's great as it allows you to go back in time to debug what may have caused the bug. But `rr` is often not great for concurrency bugs since it emulates a single-core machine. Though debugging a VM is generally a nightmare. What we desperately need is a debugger that can debug both the VM and the language running on top of it. Usually it's one or the other.

> In general I’d argue you haven’t fixed a bug unless you understand why it happened and why your fix worked, which makes this frustrating, since every indication is that the bug exists within proprietary code that is out of my reach.

Were you using Oracle GraalVM? GraalVM community edition is open source, so maybe it's worth checking if it is reproducible in that.

[1]: https://github.com/rr-debugger/rr

https://rr-project.org/ had the same problem. They use the retired conditional branch counter instead of instruction counter, and then instruction steeping until at the correct address.

That'll work great for your Distributed QSort Incorporated startup, where the only product is a sorting algorithm.

Formal software verification is very useful. But what can be usefully formalized is rather limited, and what can be formalized correctly in practice is even more limited. That means you need to restrict your scope to something sane and useful. As a result, in the real world running thousands of tests is practically useful. (Well, it depends on what those tests are; it's easy to write 1000s of tests that either test the same thing, or only test the things that will pass and not the things that would fail.) They are especially useful if running in a mode where the unexpected happens often, as it sounds like this system can do. (It's reminiscent of rr's chaos mode -- https://rr-project.org/ linking to https://robert.ocallahan.org/2016/02/introducing-rr-chaos-mo... )

The approach of check-pointing computation such that it is resumable and restartable sounds similar to a time-traveling debugger, like rr or WinDbg:

https://rr-project.org/

https://learn.microsoft.com/windows-hardware/drivers/debugge...

https://github.com/rr-debugger/rr?tab=readme-ov-file#system-...