nikhila01

Thanks for taking the time to read and respond. I admit the second paragraph of my post was a bit aggressive and I was on the fence about posting it. I don't have a problem with you sharing your background but the parts I mentioned previously came off in a certain way to me.

I found your initial argument on dynamic arrays dismissive because you admitted you had never heard of it, then implied that they don't make sense as if to justify why you had never heard of them. I find that intellectually dishonest and it really ticked me off; it's just confirming one's own bias. I still find your argument a bit dismissive although we can agree to disagree. It's not a case of worthiness to be on a list of best algorithms or of fancy math derivations. They are widely used in practice, are O(1) for many operations, work well with caches, and are worth studying for that reason.

As for making a "good contribution of my own" by reviewing the course, I don't feel the need. It's a standard undergrad algorithms course of the kind that most CS students would take. I don't think there's any value in reviewing the syllabus when they all tend to cover the same material.

I'm probably won't reply again so (sincerely) have a good day. I realize you feel attacked but if you're going to opine on something then other people might opine on your opinion. You don't hesitate in your writing style so I didn't either. I just apologize if I made it too personal. I read some things that I couldn't let slide.

MIT's discrete math course [1] is listed as a prerequisite for the algorithms course so Problem Set 0 doesn't seem unreasonable in that case.

Requiring an intro programming class and a discrete math class won't require you to delay teaching algorithms for "several years". Maybe just a semester or two.

Universities can also start teaching basic data structures and some algorithms in the programming classes. For example Stanford teaches some in CS106B Programming Abstractions [2] and then goes into more detail in CS161 Design and Analysis of Algorithms [3].

[1] https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-...

[2] https://see.stanford.edu/course/cs106b

[3] https://stanford-cs161.github.io/winter2022/

You should read about dynamic arrays more carefully. They have amortized O(1) insertion which is better than a tree, and the data is contiguous in memory which gives it better cache locality than a tree. They are one of the most popular data structures.

Parts of your post also seem to me to be quite boastful and low-value: (paraphrasing) "the course takes itself very seriously", "why spend so much time teaching so little material", "these topics are mostly old; just read Knuth", and "dynamic programming is easy; I learned it in 90 seconds and then did my PhD in it".

They were looking at IONQ+ which is what you get if you google IonQ. I guess those are the warrants. Google has the warrants as IONQ+ but Yahoo as IONQ-WT.

- https://www.google.com/finance/quote/IONQ+:NYSE

- https://finance.yahoo.com/quote/IONQ-WT

Here's a version of the slides which also has notes: https://homes.cs.washington.edu/~tom/talks/edreform.pdf

I was curious too. Probably https://careers.jpmorgan.com based on his LinkedIn and the fact that he said "Careers Page redesign for one of the biggest banks in the world."

Which is why it's fine to challenge the comment. The commenter is implying a lot considering he doesn't have any inside knowledge of Adobe Sign.

And even if you look at public data--esignatures being relatively new, Covid moving more things to digital, DocuSign's share price up 5x since their 2018 IPO, Dropbox acquiring HelloSign for $230M, Adobe's own share price up 15x in the last 10 years--there's not much to indicate that Adobe Sign is a legacy app that could just survive in maintenance mode.

There's also a tendency for people to underestimate the size and complexity of applications because they only use a fraction of the features.