81–90 of 265 posts
No Silver Bullet, by Fred Brooks http://worrydream.com/refs/Brooks-NoSilverBullet.pdf
The original STL documentation https://www.sgi.com/tech/stl/table_of_contents.html
https://www.cs.princeton.edu/~chazelle/pubs/polygon-triang.p...
Out Of The Tarpit, by Moseley and Marks https://github.com/papers-we-love/papers-we-love/blob/master... The first half of the paper is a spot-on critique of so many things that go wrong in the process of designing and implementing large-scale software systems. The second half, where the authors propose a solution, kind of goes off the rails a bit into impracticality... but they definitely point in a promising directi…
https://www.cs.ucf.edu/~dcm/Teaching/COT4810-Fall%202012/Lit...
As an architectural lighting guy, seeing realtime global illumination look this good in a game engine was fantastic. Parts of the algorithm I can understand, parts go over my head still, but the results are amazing.
A big part of what I do at work is radiosity simulations in AGI32 which is of course more accurate (because it's trying to accurately simulate real world lighting results) but much much slower.
http://research.nvidia.com/publication/interactive-indirect-...
State in Haskell. John Launchbury and Simon L. Peyton Jones
https://www.microsoft.com/en-us/research/wp-content/uploads/...
It might be a cliche one to pick, but I really really really enjoy Alan Turing's "Computing Machinery and Intelligence"[1]. This paper straddles the line between CS and philosophy, but I think it's an important read for anyone in either field. And a bonus is that it's very well-written and readable. [1] https://www.csee.umbc.edu/courses/471/papers/turing.pdf
[1]: https://raft.github.io/raft.pdf
[2]: https://www.microsoft.com/en-us/research/wp-content/uploads/...
[3]: https://www.microsoft.com/en-us/research/wp-content/uploads/...
[4]: https://www.microsoft.com/en-us/research/wp-content/uploads/...
Producing Wrong Data without Doing Anything Obviously Wrong. Immediately useful for anyone measuring compiler transformations performance!
Great paper, yes. Immediately useful? More like disheartening, because it doesn't really tell you how to be sure your measurements are OK.
[0] http://plasma.cs.umass.edu/emery/stabilizer.html "Stabilizer: Statistically Sound Performance Evaluation" by Charlie Curtsinger and Emery Berger, ASPLOS 2013
I would never call it my "all-time favorite" (no paper qualifies for that title in my book), but Satoshi Nakamoto's paper, "Bitcoin: A Peer-to-Peer Electronic Cash System" deserves a mention here, because it proposed the first-known solution to the double-spending problem in a masterless peer-to-peer network, with Byzantine fault tolerance (i.e., in a manner resistant to fraudulent nodes attempting to game the rules)…