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I do think that it was a mistake to use the word "all" and imply that there are absolutely no bugs in FoundationDB. However, FoundationDB is truly known as having advanced the state of the art for testing practices: https://apple.github.io/foundationdb/testing.html.

So in normal cases this would reek of someone being arrogant / overconfident, but here they really have gotten very close to zero bugs.

The other issue I would point out is that building a database, while impressive with their quality, is still fundamentally different than an application or set of applications like a larger SaaS offering would involve (api, web, mobile, etc). Like the difference between API and UI test strategies, where API has much more clearly defined and standardized inputs and outputs.

To be clear, I am not saying that you can't define all inputs and outputs of a "complete SaaS product offering stack", because you likely could, though if it's already been built by someone that doesn't have these things in mind, then it's a different problem space to find bugs.

As someone who has spent the last 15 years championing quality strategy for companies and training folks of varying roles on how to properly assess risk, it does indeed feel like this has a more narrow scope of "bug" as a definition, in the sort of way that a developer could try to claim that robust unit tests would catch "any" bugs, or even most of them. The types of risk to a software's quality have larger surface areas than at that level.

There's a lot of assertions that I throw into business applications that would be very useful to test in this way. So I don't think this only applies to testing databases.

Also, when properties are difficult to think of, that often means that a model of the behavior might be more appropriate to test against, e.g. https://concerningquality.com/model-based-testing/. It would take a bit of design work to get this to play nicely with the Antithesis approach, but it's definitely doable.

Just to clarify, I am definitely not saying this is only useful or only applies to databases.

The point was more that, I don't see how this testing approach (at the level that it functions) would catch all of the bugs that I have seen in my career, and so to say "all of the bugs" or even "most of the bugs" is definitely a stretch.

This is certainly useful, just like unit tests, assertions, etc are all very useful. It's just not the whole picture of "bugs".

Yes, there are plenty of non-functional logic bugs, e.g. performance issues. I think this starts to drastically hone in on the set of "all" bugs though, especially by doing things like network fault injection by default. This will trigger complex interactions between dependencies that are likely almost never tested.

They should clarify that this is focused on functional logic bugs though, I agree with that.

I’d go so far as to say it is actually impossible to do UI testing in some kind of web based product unless it came from the browser makers themselves.

I’d settle for decent heap debugging.

I think the reference to "all the bugs" here is basically that our insanely brutal deterministic testing system was not finding any more bugs after 100's of thousands of runs. Can't prove a negative obviously, but the fact that we'd gotten to that "all green" status gave us a ton of confidence to push forward in feature development, believing we were building on something solid - which, time has shown we were.

Thanks -- that's very clarifying! But isn't this circular? The lack of bugs is used as evidence of the effectiveness of the testing approach, but the testing approach is validated by...not finding any more bugs in the software?

Yeah but if your software is running in an environment that controls for a lot of non-determinism and can simulate various kinds of failures and degradations at varying rates, and do it all in accelerated time and your software is still working correctly; I think it’d be somewhat reasonable to assert that maybe the testing setup has done a pretty good job.

Agreed, the approach sounds very interesting and I can see how it could be very effective! I'd love to try it on my own stuff. That's why it's so surprising (to me) to claim that the approach found nearly every bug in something as complicated as a production distributed database. My career experience tells me (quite strongly) that can't possibly be true.

I consider a "bug" to be "it was supposed to do something and failed".

Issues around business logic are not failures of the system, the system worked to spec, the spec was not comprehensive enough and now we iterate.

...And now we could probably start debating your narrow definition of "system". ;-)

Most of the software I've built doesn't have "a spec.", but let me zoom in on specs. around streaming media. MPEG DASH, CMAF or even the base media file format (ISO/IEC 14496-12) at times can be pretty vague. In practice, this frequently turns up in actual interoperability issues where it's pretty difficult to point out which of two products is according to spec and which one has a bug.

So yes, I totally agree with GP and would actually go further: a phrase like "we found all the bugs in the database" is nonsense and makes the article less credible.

What do you call it when the spec is wrong? Like clearly actually wrong, such as when someone copied a paragraph from one CRUD-describing page to the next and forgot to change the word "thing1" to "thing2" in the delete description.

Because I'd call that a bug. A spec bug, but a bug. It's no feature request to make the code based on the newer page delete thing2 rather than thing1, it's fixing a defect

Ya, I would like a word for this as well. I naturally refer to this category of error as bug, but this occasionally leads to significant conflict with others at work. I now default to calling _almost everything_ a feature request, which is obviously dumb but less likely to get me into trouble. If there is a better word for "it does exactly what we planned, but what we planned was wrong" I would love to adopt it.

I reported such a bug to some software my company uses (Tempo). Vendor proceeds to call it a feature request because the software successfully fails to show public information (visible in the UI, but HTTP 403 in the API unless you're an admin).

Instead of changing one word in the code that defines the access level required for this GET call, it gets triaged as not being a bug, put on a backlog, and we never heard from it again obviously

We pay for this shit

Successful failure is my favorite kind, I like to think that all my failures are successful

There’s the distinction between correctness and fitness for purpose which I think is helpful for clarifying the issues here.

Correctness bug: it didn’t do what the spec says it should do.

Fitness for purpose bug: it does what the spec says to do, but, with better knowledge, the spec isn’t what you actually want.

Edit: looks like this maps, respectively, to failing verification and failing validation. https://news.ycombinator.com/item?id=39359673

Edit2: My earlier comment on the different things that get called "bugs", before I was aware of this terminology: https://news.ycombinator.com/item?id=22259973

Systems Engineering has terminology for this distinction.

Verification is "does this thing do what I asked it to do".

Validation is "did I ask it to do the right thing".

Tangentially related, but I've recently started distinguishing verification and validation in my data cleaning work:

verification refers to "is this dataset clean?" or the more precise "does this dataset confirm my assumptions about what a what a correct dataset should be given its focus"

validation refers to "can it answer my questions?" or the more rigorous "can I test my hypotheses against this dataset?"

So I find this interesting (but in hindsight unsurprising) that similar definitions are used in other fields. Would you have a source for your defintions?

They're fairly standard terms from "old style" project management - they show up in the usual V Model of Waterfall vein.

E.g. see Wikipedia: https://en.m.wikipedia.org/wiki/Verification_and_validation

A spec bug is just as bad as a code bug! Declaring a system free of defects because it matches the spec is sneaky sleight-of-hand that ignores the costs of having a spec.

The actual testing value is the difference between the cost of writing and maintaining the code, and the cost of writing and maintaining the spec.

If the spec is similar in complexity to the code itself, then bugs in the spec are just as likely as bugs in the code, thus verification to spec has gained you nothing (and probably cost you a lot).

I agree they are separate, but in my long experience, spec bugs are at least as common as your first definition.

The best definition I've heard for "bug" is "software not working as documented". Of course, a lot of software is lacking documentation -- and those are doc bugs. But I like this definition because even when the docs are incomplete, the definition guides you to ask: would I really document that the software behaves like this or would I change the behavior [and document that]? It's harder (at least for me) to sweep goofy behavior under the rug.

To be fair, the line right after that is "I know, I know, that's an insane thing to say."

I feel like business logic bugs live on a separate layer, the application layer, and it's not fair to count those against the database itself.

I agree that suboptimal query planning would be a database-layer bug, a defect which could easily be missed by the bug-testing framework.

Good summary of the hard part of being a software developer that deals with clients.

What software developer does not deal with clients (and makes a living)?

lots of software developers never deal with clients (clients as in the people who will actually use the software) - most of them in fact, in any of the big companies I have worked for anyway...and that is probably not a good thing.

I myself, prefer to work with the people who will actually use what I build - get a better product hat way.