To be fair, this book definitely doesn’t start from first principles since UIUC requires several classes before 374 (the class which uses this book). UIUC splits the data structures material into another hands-on class, and introduces discrete math and preliminary ideas about algorithm analysis and proving correctness in another course.

On top of that, 374 only uses about half this textbook in conjunction with other notes about topics not covered in this book (mostly models of computation). The rest of the material in this textbook is used in 473, the elective advanced algorithms course.

That’s not to say that your experience isn’t valid, but within the context it is primarily used in, it’s a very good additional resource to lecture content, which is more than can be said of most textbooks

So not that dissimilar from CLRS, then. Despite its introductory title it is very dense and voluminous. Almost more like a graduate level reference.

There really needs to be a text that captures the middle ground between CLRS and Grokking Algorithms and I guess this isn’t it.

I'm not familiar with Grokking Algorithms, but fwiw the most important prereq at UIUC for 374 is 173, which also happens to have a free textbook[1] written by another UIUC professor, Margaret Fleck. I consider it to be a high quality introduction to discrete math and have good memories of her as a professor as well.

[1] https://mfleck.cs.illinois.edu/building-blocks/updates-fa201...

Grokking Algorithms is an introductory illustrated book.

https://www.manning.com/books/grokking-algorithms

Perhaps Algorithms Illuminated (Roughgarden).

> I didn't not find this book useful. Somehow it managed to confuse me more.

And now you’re carrying on the tradition.

I think I had a similar experience. I suspect its because its a very unorthodox approach; the style seems more targeted towards someone with a bunch of time reading through it slowly rather than gulping it down quickly like for most undergraduate courses.

For getting me through the tests, I did end up using more traditional books. However, now, several years past academia, I find this style very engaging and delightful to read.

I worked through this one on Dan Luu's recommendation and loved it: https://www.amazon.com/gp/product/0073523402

That's one wonderfully written book.

> the style seems more targeted towards someone with a bunch of time reading through it slowly rather than gulping it down quickly like for most undergraduate courses.

Yep. That's intentional.

If you try to gulp this subject down quickly, you're much more likely to choke.

Which book ended up helping you when you were in academia?

Which one helped you learn?

For the general case, the CLRS book is recommended, but I personally found Algorithm Design by Jon Kleinberg and Eva Tardos to be the best introduction in undergrad: https://www.amazon.com/Algorithm-Design-Jon-Kleinberg/dp/032...

Despite its name CLRS goes WAY beyond an introduction

What ultimately helped you?

It's a fantastic book, but it's not worth $186.65.

That tells us a lot. ;)