yet LLMs dont do off-by-one errors, typos mixing up variable names, interesting they seem unable to learn these human patterns
They definitely write off by one errors. One of the first serious work tasks I used AI for a few months ago immediately had an off by one error.
What they are really good at is writing boilerplate and reading API documentation / example code. Avoiding subtle errors is not what they're good at in my experience.
I've seen both of those (and others besides). I don't know how much code you've looked at but your negative directly contradicts my experience. Review that code. All of it. Be super critical because it looks good but that doesn't mean it is good. Those are two entirely different things.
Also: most tests are positive tests. Tests rarely observe the negative space: that which is there but shouldn't be there.
They do those things all the time. More often than humans, in my experience.
Citation needed.
looks at particledb