venom VS rr

You can also load fixtures in database directly, work with Kafka queues both as a producer (e.g. write an event to a Kafka queue, wait a few seconds and see that it was consumed by the service you test, and that some side effects can be observed) or as a consumer (e.g. make sure after an HTTP call, an event was correctly pushed to a queue), or even read a mailbox in IMAP to check that your service correctly send an email.

It's a bit rough on the edges sometimes, but I'd never go back on writing integration tests directly in my programming language. Declarative is the way to go.

[1]: https://github.com/ovh/venom

To write and run our integration tests, we'll use Venom. Venom is a tool created and made open-source by OVHcloud: https://github.com/ovh/venom

From my experience, generated tests are worthless for anything more serious than smoke tests. I prefer working with no tests than automated tests, I feel they give you a false sense of confidence.

The Step CI engine itself looks good though. It looks like a cleaner, but less powerful version of a tool (open source, build in-house) we used when I worked at OVHcloud, Venom: https://github.com/ovh/venom

Here's an example test file for the HTTP executor of Venom: https://github.com/ovh/venom/blob/master/tests/http.yml it's very close to Step CI format.

I'd still use Venom because it's way more powerful (you have DB executors for example, so after executing a POST request you can actually check in DB that you have what you expect) and I prefer focusing on actually writing integration tests instead of generating them.

Maybe this post sounds harsh (I feel it as I write it because I have strong feelings against test generation) but I think your approach is a good one for actually writing automated tests. Testing APIs declaratively like this has a great benefit: your tests work on an interface. You can migrate your API to a whole new stack and your tests remain the same. I did it multiple time at OVHcloud: one time migrating a huge API from a Go router to another (Gin->Echo), and another time migrating public APIs from a legacy, in-house Perl engine to a Go server.

I still struggle with GDB but my excuse is that I seldom use it.

When I was studying reverse engineering though, I came across a really cool kit (which I've yet to find an alternative for lldb, which would be nice given: rust)

I'd recommend checking it out, if for no other reason than it makes a lot of things really obvious (like watching what value lives in which register).

https://github.com/hugsy/gef

LLDB's closest alternative to this is called Venom, but it's not the same at all. https://github.com/ovh/venom

We incorporated [Venom](https://github.com/ovh/venom) into our workflow. It's great for initiating and managing a suite of yaml based tests. It didn't work out of the box for us due to the heavily asynchronous nature of our system, but after a few additions, it has helped my team greatly. We were often afraid to make large changes to critical pieces of the system since a full regression test could take a week or so to check everything. Now it takes an hour.

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-...