Ask HN: Is Knuth's TAOCP worth the time and effort?

1. Most of the time you are not implementing foundational algorithms like sorting or SAT solving. You use mature implementation in libraries.

2. If you are in fact implementing foundational algorithms, then the existing volumes of Knuth cover only a very limited set of problem areas.

3. If you are implementing something in an area covered by Knuth, the books are worth looking into as a reference, but often writing performant and robust code requires considerations not in Knuth. This is because Knuth works with an idealised machine ignoring things like parallelism, memory hierarchy etc. and understandably does not get into software design issues.

I think you can read at various levels though.

When I say I've read most of Volumes 1-3, I mean literally that, I read the text through. At that level it isn't too difficult to read, and you'll learn a lot like that.

However some bits I've studied in much greater detail, like for instance the multi-precision arithmetic algorithms which I had to implement. For that I read it multiple times, implemented the algorithms, did some of the exercises. That takes much much longer than just reading it through.

It is rather like reading a research paper which you do roughly like this, stopping after any step where you think it is no longer providing value to you.

    1. Read the title
    2. Read the abstract
    3. Read the paper through quickly.
    4. Read the paper through slowly being more critical, making notes.
    5. Read the paper through again working through the maths, implementing the algorithms, making sure you understand everything.

So I've read most of TAOCP at level 3, half a volume at level 4 and only 50 pages at level 5.

If nothing else I've loaded the index in my head!

PS the examples are notorious in TAOCP. The easy ones will take a few minutes and the hard ones are unsolved research problems!

For instance, I just opened randomly to the binary tree traversal material in Vol. I. It's very mathematic or formal, e.g. "T2. [P = Λ?] If P = Λ, go to step T4." and so on. To fish out some of the more interesting details, you have to look through the questions and then flip to the answers.

Meanwhile, https://en.wikipedia.org/wiki/Tree_traversal has the same information but somehow more clearly presented.

If I flip to other random pages and scan for 30 seconds, I can't find much that is actually interesting---particularly in the early volumes.

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The Art of Electronics is more my speed, as it's a collection of real-world applications, deep dives into each component type, quick comparison tables, and clear overview of a specific design's pros and cons. It's as much interesting to read through as it is useful as a reference.

I can flip to basically any random page of The Art of Electronics and find something eliciting, "Oh cool." I can't say the same for TAOCP.