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Show HN: Checksum – generate and maintain end-to-end tests using AI

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31–34 of 34 posts

Re: Show HN: Checksum – generate and maintain end-to-end tests using AI

#31
Most tool companies making claims about their tools show a shocking lack of knowledge about testing. This generally guarantees that their tools are dismissed by serious professionals. That still leaves a pretty substantial market among credulous wishful thinkers, of course.

But as a tester, I would like to see a tool that isn’t just more bullshit. For this to happen you will have to explain:

- What exactly is your product designed to do? What kind of products can it be applied to test?

- What do you mean by the word test? Humans test in many ways and levels. Do you simply mean “exercise code while detecting crashes?” Because that’s a tiny part of testing.

- Code coverage is not the only kind of coverage. So how do you automatically achieve state and data coverage? I’m guessing you don’t, but hoping you will surprise me.

- Test oracles come in all shapes and sizes. One of the reasons I say testing cannot be automated is that I can easily demonstrate that a human tester cannot fully specify their own oracles, and thus cannot write code to implement them, either. So, how does your product recognize a bug when it sees it?

- How much human handholding is needed to operate your product?

- Testers think critically about how users interact with the product as users attempt to fulfill their purposes. This guides practical testing. I haven’t yet seen any product that thinks critically. ChatGPT can’t. So how does your product cope?

- When the product under test changes, what does your product do?

- Can your product EXPLAIN its test coverage (other than reporting code coverage, which is a poor indicator of good test coverage)?

- Say I have a product that sends the user through a multimodal questionnaire (including the use of animated screens that guide the user through measuring heartrate) and then produces a diagnosis of possible illnesses. Can your product tell if the diagnosis was correct in relation to the original intent of the logic that is documented in Jira tickets and Slack conversations? Will it generate questions about any of that, the way a real tester does?

Re: Show HN: Checksum – generate and maintain end-to-end tests using AI

#32

How is the product different from the other test generation tools? How do you check if the are testing the intended behavior. My experience with automated testing solutions has been lukewarm so far.

I agree! My experience with test generation tools was also lukewarm which is why we founded Checksum. > How is the product different from the other test generation tools We train our models based on real user sessions. So our tests are: 1. Completely auto-generated 2. Achieve high coverage of real user flows, including detecting edge cases 3. Automatically maintained and execute with our models so they are less flake…

So you are saying that your system needs me to do all the testing (it is infeasible to watch our users, because we test the product before it is released to any users) so it can learn how to test?

How can it know, by watching my clicks, how I decide if the behavior is correct on the backend?

Re: Show HN: Checksum – generate and maintain end-to-end tests using AI

#34
congrats on the launch.

0 - seriously rethink your branding. I can help.

1 - how does the Ai know when the test is successful? — is it a visual comparison? — if so.. is there a threshold range that can be adjusted?

2 - how does this differ from https://www.meticulous.ai/

3 - would it work on highly complex UX/Ui interactions like these here?

https://youtu.be/WtglzRWQzVE

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