Art of Programming - Volume 3 - Answers to Exercises

What Hacker News says

1. shaknaAug 2022
   I worked on some ancient FORTRAN for CommBank (formerly Commonwealth Bank of Australia). Most of the details are still under NDAs, but the project was amazing.

   Every variable and function was explained in a series of physical manuals in excruciating, and up-to-date, detail. The manuals had index lists by name, function, type and concept, making it ridiculously easy to find exactly what you were looking for. The documentation felt almost like reading Knuth's Art of Programming. It explained not just how a function worked, but also the dependencies and how they worked on that particular hardware, including pieces of the FORTRAN standard library.

   On top of that nugget of most people's fantasies, there was actually a test suite! It wasn't written by the original authors, and had been pieced together over the years. But it was a testsuite for code running on a mainframe the size of a small room. Since when do you ever get tests for code written in the 70s!?

   Working for CommBank was hard - the standards for absolutely everything that they have and do are A-grade. A single complaint from a coworker or customer can land you in front of a review board. But the work they produced, at least what I saw, is absolutely worth it.

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2. jhbadgerJul 2019
   Indeed. Many people are turned off by reading Knuth because his "Art of Programming" deals with tasks, such as sorting, that are viewed as menial and (almost) never implemented by hand these days. But there was a lot of math involved in figuring out how to make such tasks as efficient as possible, as Knuth shows. Theoretical computer science is math (but then so is much of theoretical anything).
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3. hackermailmanMar 2018
   One discrete math book I liked was this one https://cs.wheaton.edu/~tvandrun/dmfp/

   It's heavy on sets and functions, turning sets into types to manipulate in Standard ML so the reader can understand what's going on intuitively. I also liked Knuth's crash course in The Art of Programming and it is hard to read other books when you're used to Knuth's clear and precise explanations mixed with dry humor keeping you engaged.

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4. tannhaeuserJun 2017
   +1 for the "dragon book". Though the criticism about it being too focused on lex/yacc-era compilers and not being relevant today might have a point, I still find the mix of pragmatism and formal language theory absolutely worth the read, stylish/Unix-y, and even entertaining - for me, truly a hallmark of "American-style" comp.sci. standard literature (as opposed to more theoretical expositions to the topic).

   Also, Donald Knuth's "The Art of Programming" (at least the fundamental and sorting/searching algorithms books), plus a book about graph theory and algorithms.

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5. ShrikenJan 2017
   There are quite a few great books on stable information. To name a couple: Knuth's Art of Programming, Structure and Interpretation of Computer Programs, Advanced Systems Programming in the Unix Environment, the dragon book. Why should I own them physically? Well, I find physical books more comfortable to read than digital ones. They lack text search, but being able to have it open on my desk next to my computer is handy. Not to mention the sleep hygiene issues from using a screen before going to sleep.
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6. hibikirOct 2016
   If I have to do a very careful performance decision on something as well trodden as a sorting algorithm, I'll walk to the bookshelves, pick up The Art of Programming, Volume 3, and let Knuth handle it for me.

   As a software engineer, there are things I do all the time: Reading unfamiliar code and third party documentation, do some debugging (often based on logs), and try to write code that is well factored and thoroughly tested. I want to know whether any prospective teammate is good at those things for their experience level.

   Interestingly enough, the general algorithm questions are easier the newer you are, and the less you know about all the topics I mentioned, because more often than not those are learned on the jobs, while the basic algorithms are learned in college. I end up reading papers on algorithms at work, but they are not algorithms that I expect to be general knowledge, and that I'd expect people to read on the job when they are applicable: How many candidates are going to be able to explain hyper log log, Paxos or Lamport clocks on command? Is knowing all of those three by heart a sensible pass/no pass signal? I for one don't think so.

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