bishboria

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

macintux

• https://ferd.ca/a-distributed-systems-reading-list.html
• http://the-paper-trail.org/blog/distributed-systems-theory-for-the-distributed-systems-engineer/
• https://github.com/palvaro/CMPS290S-Winter16/blob/master/readings.md
• http://muratbuffalo.blogspot.com/2015/12/my-distributed-systems-seminars-reading.html
• http://christophermeiklejohn.com/distributed/systems/2013/07/12/readings-in-distributed-systems.html
• http://michaelrbernste.in/2013/11/06/distributed-systems-archaeology-works-cited.html
• http://rxin.github.io/db-readings/
• http://research.microsoft.com/en-us/um/people/lamport/pubs/pubs.html
• http://pdos.csail.mit.edu/dsrg/papers/
• http://scalingsystems.com/2011/09/07/reading-list-for-distributed-systems/

Icelandjack

Reddit discussion.

Disclaimer 1: Type classes are great but they are not the right tool for every job. Enjoy some balance and balance to your balance.

Disclaimer 2: I should tidy this up but probably won’t.

Disclaimer 3: Yeah called it, better to be realistic.

Type classes are a language of their own, this is an attempt to document features and give a name to them.

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

biboudis

2016

1. Sixth Summer School on Formal Techniques / 22-27 May
2. Twelfth International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems / 10-16 July 2016
3. Oregon Programming Languages Summer School / 20 June-2 July 2016
4. The 6th Halmstad Summer School on Testing / 13-16 June, 2016
5. Second International Summer School on Behavioural Types / 27 June-1 July 2016
6. Virtual Machines Summer School 2016 / 31 May - 3 June 2016
7. ECOOP 2016 Summer School

2015

acolyer

Internet Scale Services Checklist

A checklist for designing and developing internet scale services, inspired by James Hamilton's 2007 paper "On Desgining and Deploying Internet-Scale Services."

• http://mvdirona.com/jrh/talksandpapers/jamesrh_lisa.pdf

Basic tenets

• Does the design expect failures to happen regularly and handle them gracefully?
• Have we kept things as simple as possible?

rygorous

Why do compilers even bother with exploiting undefinedness signed overflow? And what are those
mysterious cases where it helps?

A lot of people (myself included) are against transforms that aggressively exploit undefined behavior, but
I think it's useful to know what compiler writers are accomplishing by this.

TL;DR: C doesn't work very well if int!=register width, but (for backwards compat) int is 32-bit on all
major 64-bit targets, and this causes quite hairy problems for code generation and optimization in some
fairly common cases. The signed overflow UB exploitation is an attempt to work around this.

copumpkin

module Prime where

open import Coinduction

open import Data.Empty
open import Data.Nat
open import Data.Nat.Properties
open import Data.Nat.Divisibility
open import Data.Fin hiding (pred; _+_; _<_; _≤_; compare)
open import Data.Fin.Props hiding (_≟_)

jashkenas

Spurred by recent events (https://news.ycombinator.com/item?id=8244700), this is a quick set of jotted-down thoughts about the state of "Semantic" Versioning, and why we should be fighting the good fight against it.

For a long time in the history of software, version numbers indicated the relative progress and change in a given piece of software. A major release (1.x.x) was major, a minor release (x.1.x) was minor, and a patch release was just a small patch. You could evaluate a given piece of software by name + version, and get a feeling for how far away version 2.0.1 was from version 2.8.0.

But Semantic Versioning (henceforth, SemVer), as specified at http://semver.org/, changes this to prioritize a mechanistic understanding of a codebase over a human one. Any "breaking" change to the software must be accompanied with a new major version number. It's alright for robots, but bad for us.

SemVer tries to compress a huge amount of information — the nature of the change, the percentage of users that wil

dorchard

(by Dominic Orchard, School of Computing, University of Kent, 2018)

Disclaimer: this advice is non exhaustive, and every piece of advice might not suit you. At least, I hope it helps you to think about how you can develop your own strategy for exam preparation.

My top tip is to see exams as formative rather than purely about assessment. This is an opportunity to force yourself to learn a topic deeply, which will then benefit you in the future, rather than a box ticking exercise to get a fancy piece of paper at the end. This will orient your attitude to maximising your potential.

Exams are hard. They occupy a short space of time in your whole life but they can have a big impact on the rest of it, so make the most of them. Study well and study wisely.

Exam preparation