EMemmanueloga_·Jan 3, 2024
From all these I feel like the best intro is Sedgewick & Wayne. CLRS is less solo-learner friendly, in my opinion. I skimmed Erickson and I liked it too.
In the "friendly+actually-useful" category, you missed "Open Data Structures" [1] ... I think it has one of the best descriptions of trees, including B-Trees which seem to be only superficially described in other books. The "Think" series is also pretty good and covers more than just algorithms [2].
TAOCP, Okasaki, Bird: these feel really academic and/or less useful for industry work. Reading HTDP wasn't as useful to me, at least: I feel like Felleisen's books describe what he "imagines" would be a good way to write software on a "real" job :-p (non-academic setting).
Skiena: I have mixed feelings about it... It seems to have gained popularity since Steve Yegge's blog post about Google i
Read the rest
nterviews, but imho many concepts in that book are better explained elsewhere. I suppose the intended purpose of the book was to serve as a reference and an index to other resources. However, it often refers to sources that are 10 years old or older, academic implementations that could be challenging to apply in a real job setting, or things that are no longer available online afaict (e.g., LEDA), or hard to read papers, most of which lack a working implementation of the described concepts, etc. I wonder if anybody can really vouch for it or have a personal anecdote of the book being useful or enjoyable.
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1: https://github.com/patmorin/ods
2: https://greenteapress.com/wp/