Ancestors

Written by Sy Brand on 2024-12-14 at 00:06

The cover for my book on how debuggers work is here!

Preorders are still 25% off: https://nostarch.com/building-a-debugger

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Written by lopta on 2024-12-14 at 01:09

@TartanLlama I feel like debuggers are something I missed out on by not taking a CS degree, like unit testing.

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Toot

Written by Lesley Lai on 2024-12-14 at 03:02

@lopta @TartanLlama Pretty sure that CS degrees typically don't have those 😅

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Descendants

Written by lopta on 2024-12-14 at 03:07

@lesley @TartanLlama Really? That's odd.

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Written by crazyeddie on 2024-12-14 at 07:16

@lopta @lesley @TartanLlama Not really. Linear Algebra, Calculus, Discrete Math, BigO, how function calls work, kleen star and friends, a spattering of UML, Mythical Man Month, Turing Machines, the halting problem, and street fighting. Almost all of it pretty much useless in practical application.

I did decide to go torture myself with self-study and learn MIX machine code from TAOCP. I use that on a daily.

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Written by Lesley Lai on 2024-12-14 at 08:17

@crazyeddie @lopta @TartanLlama Typical university degrees often cover some system programming topics, such as data representation, assembly (usually x86), memory hierarchy, concurrency (though typically limited to C-style threads and locks), OS, virtual memory, and networking. However, I’ve never encountered university courses that delve into the implementation details of a debugger.

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Written by Lesley Lai on 2024-12-14 at 08:19

@crazyeddie @lopta @TartanLlama I agree that much of the theoretical computer science taught is pretty much useless (though, for some reason, tech interviewers love asking about it). Personally, if I need to learn theoretical stuff, I’d rather spend that time learning math instead.

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Written by lopta on 2024-12-14 at 13:12

@lesley @crazyeddie @TartanLlama I mostly meant how to use a debugger rather than how to build one.

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Written by lopta on 2024-12-14 at 13:11

@crazyeddie @lesley @TartanLlama I know what some of those things are. What's is "BigO"?

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Written by Lesley Lai on 2024-12-14 at 13:50

@lopta @crazyeddie @TartanLlama An estimation on how an algorithms' runtime or space requirement grow when the input grow. I wouldn't see it is useless, but it is often an oversimplification of the nuances of the real world.

https://en.wikipedia.org/wiki/Big_O_notation

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Written by lopta on 2024-12-14 at 13:55

@lesley @crazyeddie @TartanLlama Thanks. It sounds like a rudimentary efficiency dipstick.

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Written by crazyeddie on 2024-12-14 at 16:03

@lopta @lesley @TartanLlama It's deceiving. It's based on theory rather than practice. It can be quite wrong. For example, BigO says that inserting items into the middle of a list is faster than inserting them into a vector. Because of caching and lookahead though, and the fact that memory redirects counter that, it is more often faster to insert in the vector. BigO does not take these things into account and just counts the loops in your code.

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