alt Hacker NewsI would argue that the word "proof" in the title might be misleading you.
From the post and the example he links, the point is that if you don't at least look at the running code, you don't know that it works.
In my opinion the point is actually well illustrated by Chris's talk here:
https://v5.chriskrycho.com/elsewhere/seeing-like-a-programme...
(summary of the relevant section if you're not going to click)
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In the talk "Seeing Like a Programmer," Chris Krycho quotes the conductor and composer Eímear Noone, who said:
> "The score is potential energy. It's the potential for music to happen, but it's not the music."
He uses this quote to illustrate the distinction between "software as artifact" (the code/score) and "software as system" (the running application/music). His point is that the code itself is just a static artifact—"potential energy"—and the actual "software" only really exists when that code is executed and running in the real world.
> if you don't at least look at the running code, you don't know that it works.
Your tests run the code. You know it works. I know the article is trying to say that testing is not comprehensive enough, but my experience disagrees. But I also recognize that testing is not well understood (quite likely the least understood aspect of computer science!) — and if you don't have a good understanding you can get caught not testing the right things or not testing what you think you are. I would argue that you would be better off using your time to learn how to write great tests instead of using it to manually test your code, but to each their own.
What is more likely to happen is not understanding the customer needs well enough, leaving it impossible to write tests that align with what the software needs to do. Software development can break down very quickly here. However, manual testing does not help. You can't know what to manually test without understanding the problem either. However, as before, your job is not to deliver proven code. Your job is to solve customer problems. When you realize that, it becomes much less likely that you write tests that are not in line with the solution you need.