Ask HN: What was the best CS paper you read in 2017?
11–20 of 131 posts
Re: Ask HN: What was the best CS paper you read in 2017?
#12* What Developers Want and Need from Program Analysis - An Empirical Study * Weird machines, exploitability, and provable unexploitability * What You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices
* Weird ...: http://ieeexplore.ieee.org/document/8226852
* What You ...: http://s3.eurecom.fr/docs/ndss18_muench.pdf
Re: Ask HN: What was the best CS paper you read in 2017?
#13Re: Ask HN: What was the best CS paper you read in 2017?
#14Does anyone have any suggestions on finding CS papers worth reading beyond those papers listed here?
For example, I'm interested in human-computer interaction so I read CHI and UIST papers each year, and for software engineering I read ICSE and FSE.
Re: Ask HN: What was the best CS paper you read in 2017?
#15https://www.cl.cam.ac.uk/~srk31/research/papers/kell17some-p...
Re: Ask HN: What was the best CS paper you read in 2017?
#16"Toward Principles for the Design of Navigation Affordances in Code Editors: An Empirical Investigation" (http://dl.acm.org/authorize?N37917)
"The Patchworks Code Editor: Toward Faster Navigation with Less Code Arranging and Fewer Navigation Mistakes" (http://dl.acm.org/authorize?N84177)
Re: Ask HN: What was the best CS paper you read in 2017?
#17Re: Ask HN: What was the best CS paper you read in 2017?
#18https://www.sigops.org/sosp/sosp09/papers/klein-sosp09.pdf
seL4 is about 9000 LOC. So this gives a good indication of what formal verification (Isabelle/HOL) is currently capable of. seL4 is also quite fast as a result of removing unnecessary checks.
seL4 is smaller than L4Ka::Pistachio and it's also capability based which L4 isn't. They could have called it L5 or seL5.
Re: Ask HN: What was the best CS paper you read in 2017?
#19"Memcomputing NP-complete problems in polynomial time using polynomial resources and collective states" http://advances.sciencemag.org/content/1/6/e1500031.full
Could you tell us a bit about the reñevance of this work?
"We show an experimental demonstration of an actual memcomputing architecture that solves the NP-complete version of the subset sum problem in only one step and is composed of a number of memprocessors that scales linearly with the size of the problem. We have fabricated this architecture using standard microelectronic technology so that it can be easily realized in any laboratory setting"
This is traditionally what people look to quantum computing to solve, but that seems much farther off in practice that the technology described here, at least, as described.
TL;DR Memcomputing has been shown to have the same power as non-deterministic turing machines. They claim to have made some real ones with promising results. It looks like it's getting commercialized over at http://memcpu.com/.
I'm just summarizing the papers/data, not commenting on it for real, it could all just be snake oil
Re: Ask HN: What was the best CS paper you read in 2017?
#20I highly recommend people give this paper a read. I think it points the way to a radical redesign of fundamental parts of the system stack over the next 5-10 years. If you work in systems and you aren’t thinking about this stuff, you’re about to be lapped. The Case for Learned Index Structures: https://arxiv.org/pdf/1712.01208v1.pdf