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Most Influential Papers in Computer Science History

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Re: Most Influential Papers in Computer Science History

#61
post #48
post #44

Earlier quoted context omitted.

indeed this was itching me, too. I wonder how pagerank was influential to CS as a field? even mapreduce is more a rally clever technique than a boundary pushing or boundary identifying extension of the field. unlike, say, CSP --- which is missing in the list. still unlike the conciseness and structure of the list. it could evolve into a nice book :-D

If you haven’t read the pagerank paper, you should. It’s not an obvious thing. Agreed about map reduce though.

thanks for the nudge :-)

My understanding of the term "history of CS" would be "how CS evolved", as a field. How do we think about "processing 'data' with computers". what can we compute? what are limitations in how fast we can compute? how to we talk about and present algorithms, prescriptions for these computations? how do we talk about data and how we structure it (leading to SQL, and sgml/xml/JSON)?

Pagerank in contrast is a very specific type of breakthrough, a breakthrough for it's application domain. But it's not a breakthrough for how we compute or how we think about computation.

does that make sense?

Re: Most Influential Papers in Computer Science History

#62

>Go To Statement Considered Harmful” (1968) – Edsger Dijkstra This is outdated and does not apply to modern goto. It is often misunderstood which causes people to avoid goto even when it is very valid, even better than alternatives solution

How does a modern goto differ from a traditional goto?

Re: Most Influential Papers in Computer Science History

#64

>Go To Statement Considered Harmful” (1968) – Edsger Dijkstra This is outdated and does not apply to modern goto. It is often misunderstood which causes people to avoid goto even when it is very valid, even better than alternatives solution

To my understanding, the underlying issue is the way to structure code in a maintenance friendly way. It’s just very easy to go awry with unrestricted wild goto. There are more often than not some alternatives control flows which are easier to mentally follow. And things like label in Java[1] already capture most of relevant cases in which a generic goto statements might feel like a valid approach. This doesn’t mean that there is absolutely no case where a goto might be the most elegant easiest way to implement something, but that few cases are exceptional.

I mean, no one feels like using a laser is a proper way to cut butter, but using lasers is sometime the best cutting accurate option.

[1] https://www.geeksforgeeks.org/g-fact-64/

Re: Most Influential Papers in Computer Science History

#65
post #33
post #29

> He sketches out a hypothetical “Turing Machine,” proving that, if something is computable at all, a machine (in principle) can handle it. That's not what Turing proved. Instead, what he proved in his paper was that there are some problems which aren't solvable by Turing Machines (and therefore presumably by any machine). That's the Entscheidungsproblem (decision problem) referenced in the title. What TFA references…

And in 100 years we have gone completely the opposite direction in terms of where we think artificial intelligence lies. Rather than constructing a machine with all the known truths, modern searching for artificial intelligence using machines is mostly sifting through human commentary to create an organized feuilleton machine versus Leibniz's axiomatic approach

No, Turing had precisely that approach of feeding the machine with learning material in mind[1], but you have to build a machine apt to consume generic knowledge body before you throw at it anything.

https://philsci-archive.pitt.edu/9085/1/SterrettBringingUpTu...

Re: Most Influential Papers in Computer Science History

#66

>Go To Statement Considered Harmful” (1968) – Edsger Dijkstra This is outdated and does not apply to modern goto. It is often misunderstood which causes people to avoid goto even when it is very valid, even better than alternatives solution

How does a modern goto differ from a traditional goto?

"Modern" goto (well, there aren't many modern languages with goto, but anyway) is semi-structured. Most importantly, it's local: you cannot jump into or out of subroutines, which was Dijkstra's major peeve. Using goto for backwards jumps is also usually discouraged post-Dijkstra.

Re: Most Influential Papers in Computer Science History

#67

I actually found this to be an odd mix. Are we selecting papers that had an influence on computer science (as in, the theory of computation), or that had an impact on technology? Or are we just using CS as a catch-all for "all things computer"? The Turing paper is foundational for CS, but without it, would the technology have evolved differently? Probably not. Most software engineers have not read it. Conversely, the…

Something doesn't feel quite right to me seeing the PageRank paper in a short list alongside Turing and Shannon's foundational work on computability and information theory. “On Computable Numbers, with an Application to the Entscheidungsproblem” is almost 90 years old at this point and just as true and relevant now as it was then. Is PageRank even as relevant today as it was in 1998, let alone another 50 years from n…

Will it be directly influential in 50 years from now on? Maybe no.

But, indirectly looking, it influenced establishment of Google, which influenced many thousands of innovations in this field.

So yes, PageRank is hugely influential in my opinion.

Re: Most Influential Papers in Computer Science History

#68

Please add Satoshi Nakamoto, for Bitcoin and the money revolution

Idk why it is downvoted tbf Bitcoin paper is really interesting from CS perspective And also had HUGE influence on the world

No, sorry, you are deluded. Compared to the ones from Shannon, Knuth, Ritchie, John McArthy... BTC barely maked a dent.

Re: Most Influential Papers in Computer Science History

#69

Love this, agree w/ all. Probably just needs to be a bigger list. Unix paper. Hinton on deep learning (pick one). Map Reduce + GFS from Google. Paxos from dist systems. PGP paper; RSA paper

Lisp from McArthy.

Plan9+CSP.

Both, maybe, polar opposites, but complementary.

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