I'm not sure if TAoCP is "workplace on the job" material.
TAoCP is aiming at damn near "perfection" of programming. Donald Knuth is analyzing the exact assembly language of all of his decision-making with these algorithms. The assembly language is represented as a random variable, and an _exact_ count of those assembly language statements (in loops and other complex jumps) is analyzed.
Everything from the highest-level algorithm design / mathematical concepts is discussed... down to the lowest-level assembly level details / implementation of the code. And everything in between.
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As such, when Knuth / TAoCP covers a subject, it feels comprehensive, in a way that no other writer has ever accomplished.
So how does this work out in practice? Well, there's plenty of tutorials on hash tables out there. But only Knuth's writing on Hash tables / linear probing has ever hit the entire subject for me.
Other books will go over linear probing vs quadratic probing vs double-hashing. Meanwhile, Knuth carefully derives the formulas of each, and how it changes at the assembly level implementation.
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Is that useful for workplace environment? Probably not. In work, you only need to know "Linear Probing Hash Tables work like this, do it", and maybe not the analysis of it.
But if you're doing more fundamental programming, such as "GPU Implementation of Hash Table", something that very few other people have done... the Knuth-level analysis is the only thing that hits "rock bottom" and gives me all the insight "behind" the data-structure and its design.
I'd say Knuth's stuff is for people who invent new fundamental data-structures or other implementation details like that. Its not for typical workplace programming.
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For anyone who wants to know Knuth's writing style, I think his writing on Alpha-beta pruning (from the 1970s) is an excellent introduction to Knuth's writing style.
"An Analysis of Alpha-Beta Pruning" by Knuth / Moore, 1975.
Alpha-beta pruning always was kinda mystical to me. But Knuth recognizes the intermediate steps needed to understand the subject fully. The brilliance of discussing F1 (branch-and-bound) before discussing F2 (alpha-beta pruning) cannot be understated.
Knuth recognized that branch-and-bound is what most people thought of by Alpha-beta pruning. But then comes up with specific examples where F2 (true alpha-beta pruning) makes a difference over F1. And then uses math to demonstrate how often these cases come up.
Does it help in implementing AB pruning? I dunno. But it helps a lot if you wanna change AB pruning / change the fundamental search and understand why things are done that way. You only need to study "F2" if you're copy/paste programming. But the study and analysis into "F1" (branch and bound) holds deeper understandings to the entire concept of search trees.
TAoCP is aiming at damn near "perfection" of programming. Donald Knuth is analyzing the exact assembly language of all of his decision-making with these algorithms. The assembly language is represented as a random variable, and an _exact_ count of those assembly language statements (in loops and other complex jumps) is analyzed.
Everything from the highest-level algorithm design / mathematical concepts is discussed... down to the lowest-level assembly level details / implementation of the code. And everything in between.
-----------
As such, when Knuth / TAoCP covers a subject, it feels comprehensive, in a way that no other writer has ever accomplished.
So how does this work out in practice? Well, there's plenty of tutorials on hash tables out there. But only Knuth's writing on Hash tables / linear probing has ever hit the entire subject for me.
Other books will go over linear probing vs quadratic probing vs double-hashing. Meanwhile, Knuth carefully derives the formulas of each, and how it changes at the assembly level implementation.
-----
Is that useful for workplace environment? Probably not. In work, you only need to know "Linear Probing Hash Tables work like this, do it", and maybe not the analysis of it.
But if you're doing more fundamental programming, such as "GPU Implementation of Hash Table", something that very few other people have done... the Knuth-level analysis is the only thing that hits "rock bottom" and gives me all the insight "behind" the data-structure and its design.
I'd say Knuth's stuff is for people who invent new fundamental data-structures or other implementation details like that. Its not for typical workplace programming.
--------
For anyone who wants to know Knuth's writing style, I think his writing on Alpha-beta pruning (from the 1970s) is an excellent introduction to Knuth's writing style.
"An Analysis of Alpha-Beta Pruning" by Knuth / Moore, 1975.
Alpha-beta pruning always was kinda mystical to me. But Knuth recognizes the intermediate steps needed to understand the subject fully. The brilliance of discussing F1 (branch-and-bound) before discussing F2 (alpha-beta pruning) cannot be understated.
Knuth recognized that branch-and-bound is what most people thought of by Alpha-beta pruning. But then comes up with specific examples where F2 (true alpha-beta pruning) makes a difference over F1. And then uses math to demonstrate how often these cases come up.
Does it help in implementing AB pruning? I dunno. But it helps a lot if you wanna change AB pruning / change the fundamental search and understand why things are done that way. You only need to study "F2" if you're copy/paste programming. But the study and analysis into "F1" (branch and bound) holds deeper understandings to the entire concept of search trees.
Even if you never, ever, ever will program F1.