If you find a bug, you find it because you discover that a given input does not lead to the expected output.
You have to find all those ifs in your code because one of them is wrong (probably in combination with a couple of others).
If you push all your conditionals up as close to the input as possible, your hunt will be shorter, and fixing will be easier.
You don’t need to know all of the call chains because you’ve established a “narrow waist” where ideally all things have been made clear, and errors have been handled or scoped. So you only need to know the call chain from entry point to narrow waist, and separately narrow waist till end.
[0] Source: Abraham Lincoln. (At least I have heard he said that.)
> with admirable tunnel vision, bullheadedness and mission for maximally general algebraic and arbitrary constraint type systems.
I believe they're called keyhole optimizations, greedy search, and "the customer is always right..."You just can't enforce those assumptions.
https://lexi-lambda.github.io/blog/2019/11/05/parse-don-t-va...
If instead of validating that someone has sent you a phone number in one spot and then passing along a string, you can as easily have a function construct an UncheckedPhoneNumber. You can choose to only construct VerifiedPhoneNumbers if the user has gone through a code check. Both would allow you to pluck a PhoneNumber out of them for where you need to have generic calling code.
You can use this sort of pattern to encode anything into the type system. Takes a little more upfront typing than all of those being strings, but your program will be sure of what it actually has at every point. It's pretty nice.
It's really about finding the entry points into your program from the outside (including data you fetch from another service), and then massaging in such a way that you make as many guarantees as possible (preferably encoded into your types) by the time it reaches any core logic, especially the resource heavy parts.