Slashdot Mirror
Great Computer Science Papers?
slevin writes "Recently I listened to a talk by Alan Kay who mentioned that many 'new' software ideas had already been discovered decades earlier by computer scientists - but 'nobody reads these great papers anymore.' Over the years I have had the opportunity to read some really great and thought-provoking academic papers in Computer Science and would like to read more, but there are just too many to sort through. I'm wondering what great or seminal papers others have encountered. Since Google has no answers, perhaps we can come up with a list for the rest of the world?"
"The UNIX Time-Sharing System," by Dennis Ritchie & Ken Thompson, is one of the best-written papers ever. The elegance of thought and economy of description set a standard we should all aspire to.t ml
t ml
http://cm.bell-labs.com/cm/cs/who/dmr/cacm.h
I list several more classics on my "Software Engineering Reading List" page at
http://www.multicians.org/thvv/swe-readings.h
What about the work of Edsger Dijkstra? His seminal work on 'The GOTO statement considered harmful', the Shortest Path Algorithm, and the dining philosophers.
The truth is rarely pure and never simple. Oscar Wilde (1854 - 1900)
If nobody reads those "great old papers" any more, there's probably a reason. Sometimes the ideas have been superceeded; sometimes they weren't any good to begin with; often the papers are simply really hard to understand. The fact that people seriously suggest reading "great papers" reflects on the immaturity of the field; in a field like mathematics, hardly anyone ever reads the original papers (even for work done in the 20th century), instead opting to read someone else's simplification/clarification of the ideas.
We speak of the TAoCP as "the bible", but I'm not sure if there are any "new" ideas there; rather, the value of TAoCP is as a compilation and exposition of all the best ideas other people have produced.
Learn about great algorithms; don't worry about reading great papers.
Tarsnap: Online backups for the truly paranoid
Alan Turing was a genius, pure and simple.
His crypto work during the war was massively significant in winning the battle of the Atlantic, his ideas on programming, AI, neural networks, and the more-public "turing test" were breathtaking and groundbreaking. Less well known is his theory of non-linear biology, and some exceptional papers in physics. A modern version of the renaissance scientist, the michaelangelo of his day.
The hounding of him (because he was gay), arrest, loss of clearance, and subsequent suicide by cyanide in '54 was a shameful treatment of one of the most brilliant men in science this century.
Simon.
Physicists get Hadrons!
ACM and IEEE are just the places I would look for such papers. The proceedings of ACM SIGCOMM for example are a very good "filter" for the flood of papers on networking.
You betcha. There has been a lot of research over the past 50 years, and much of it ignored - especially research that isn't in English.
A lot of old research is interesting in terms of Patent law. A lot of this research can be used to invalidate patent cliaims - prior art. An idea published 30 years ago simply cannot be legitimately patented now.
Very recently my Dad told me about a new patent assigned to one of his competitors. But my Dad claimed that his colleauge didn't patent that very idea in the 1970s because my dad knew of prior art - my dad had heard a researcher from Germany talk about the same thing at a small conference.
Given prior art, my Dad and his colleauge didn't apply for patent back then. But 35 years later, a company patented the idea. My Dad was pretty pissed!
So Dad and I shlogged through tons of (paper) documents and LoC and other resources trying to help him remember who the speaker was and where the conference was held. After a few weeks of digging, we got a copy of the (hard to locate) conference proceedings, and now that brand new patent looks like it's toast.
Now here's the rub - the only reason why this patent was invalidated was because my dad is still in the industry - and he's well over retirement age. Everyone else my Dad works with thought the patent would toast them. Only my dad, and old researcher with a good memory, could help his company overcome the (invalid) patent. What if my dad was retired? What if he didn't attend that talk in the 1970s? Most people simply wouldn't have known where to look for the prior art. [And not every call for prior art is suitable for Slashdot.]
Old research and old researchers are good - not only for disposing of "new" patents, but for the value of the efforts and lessons learned. So much is forgotten.
This is shameless self-promotion, but you should read my book!
Technomanifestos discusses the truly thought-provoking, inspirational, seminal computer papers of the 20th century, from Turing's "On Computable Numbers" and "Computing Machinery and Intelligence", to Alan Kay's "Personal Dynamic Media" to Larry Wall's States of the Perl Onion.
The book delves into the historical, biographical, and scientific context of works such as these and follows the thread of inspiration to today's world. If you want to know where the Internet germinated, or how Marshall McLuhan and Pierre de Chardin influenced the World Wide Web (or even who McLuhan and de Chardin are!) you should pick up my book. And then read it.
Technomanifestos tracks the evolution of the MIT hacker, from the dapper Boston Brahmin Vannevar Bush to the famously unkempt Richard Stallman, and introduces the cast of lesser-known (to the non-Slashdot world) but crucially inventive individuals such as Ivan Sutherland and Seymour Papert.
Moreover, it discusses how the truly great computing ideas come from people who recognize that technology, especially information technology, has the power to transform people and society--these are (in the words of similarly great books) tools for thought and dream machines.
Or if you have no interest in helping me pay my DSL bill, you can go straight to the sources, many of which are available online.
author,
Does anyone know of a website where you can get access to comp sci and comp eng papers and stuff?
Try looking at arxiv.org and CiteSeer.
OS Reviews: Free and Open Source Software
I ponder if we made a list of oh say 'n' of these if the typical /.er would read them....
/. "wild herd" post questions and comments, and let them moderate up the ten or fifteen most important questions for your perusal.
We came to the conclusion that the wild herd [on Slashdot]... generally thinks that education is mostly worthless....
If I were working this space (putting my teaching hat back on) I'd cover:....
So put your money (time is money) where your mouth is.
Seriously. Email one of the Slashdot editors, get a section called "Slashdot Tells", and post your first lecture, along with assigned reading.
Let the
Come back the next week, post your answers and your next lecture, and let those who can demonstrate mastery of your earlier lecture and the assigned reading go through the cycle again.
I'll take part in whatever you care to teach, and I'd wager you'd get a core group who would follow the lecture series through.
Use a free e-text (such as the MIT open courseware), or some GFDL book, as your text.
What's in it for you? Well, teaching is the best way to learn (or re-learn). Keeps the mind supple. Not to mention the satisfaction of passing on what you know.
And telling your collegues you've learned to herd cats.
Opinions on the Twiddler2 hand-held keyboard?
Donald Knuth has written a lot of interesting papers, but his paper on TeXs line-breaking algoritm
and as far as I know, the algoritm is still state of the art and is used only by TeX, InDesign and an addition to QuarkXPress.
-- Rolf Lindgren, cand.psychol
As a PhD student, I often have to look for papers in the computer science field ; and very often, CiteSeer yields better results - or, rather, different results, but with a very good cross-referencing system. You can directly jump to the other papers cited by the paper you're reading, and you can see which papers did cite it, too.
The URL :
http://citeseer.nj.nec.com/cs
That said, I often find very interesting ideas in scientific papers, but sometimes things can't be implemented with current technology (I'm still talking about computer science domain, since that's what I know), or sometimes, the good idea in the paper is obsoleted a few years later.
For instance, I remember a scheduling algorithm to read disk blocks in a Video-On-Demand server : it was maybe very clever when it was written, when they had to feed 155 Mbps with a computer having 16 MB of RAM, but today, you have maybe 10 times more throughput, but 100 times more RAM - so you can use simpler, memory-hungry, buffering methods.
The problem is, that it's difficult (IMHO) to say "OK, this paper is theoretically interesting, but we can't implement this today, BUT we will probably be able to do it in a few (dozen) years", because you don't know what will and won't evolve (in my previous example, it was easy to predict that network bandwidth and memory size would increase, but it was maybe harder to guess that MPEG4 and DivX would allow the bitrate of a video stream to stay low...)