LukeMathWalker

name: Security audit
on:
  schedule:
    - cron: '0 0 * * *'
  push:
    paths:
      - '**/Cargo.toml'
      - '**/Cargo.lock'
jobs:
  security_audit:

formix

/****************************************************************************
 * Copyright 2009-2015 Jean-Philippe Gravel, P. Eng. CSDP
 * 
 * Modified 4/7/16 - Jean-Philippe Gravel (@formix) - Moved random number
 * generator into the method "if" statement.
 * 
 * Modified 6/8/15 - Osric Wilkinson (@Moosemorals) - No point messing with
 * random seeds. Just use SecureRandom.
 * 
 * Licensed under the Apache License, Version 2.0 (the "License");

xeno-by

// PROBLEM STATEMENT

// Let's build Proxy[T], an object that can capture calls to methods of an underlying object.
// We want the proxy to be type-safe, i.e. we need to verify that the names of the calls
// and the arguments that are passed to those calls are well-typed wrt the type of the proxee.

object Test extends App {
  trait Foo { /* ... */ }
  val proxy: Proxy[Foo] = ???
  proxy.bar()

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

axt

package hu.axt.iotrace;

import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.ACC_FINAL;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.ACC_PRIVATE;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.ACC_PUBLIC;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.ACC_STATIC;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.ACC_SUPER;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.ILOAD;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.INVOKESPECIAL;
import static com.sun.xml.internal.ws.org.objectweb.asm.Opcodes.INVOKESTATIC;

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/

ragingwind

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

• Introduce Gizzard of Twitter - 트위터의 새로운 분산 관리 라이브러리 Gizzard를 소개합니다.
• The Architecture Twitter Uses to Deal with 150M Active Users, 300K QPS, a 22 MB/S Firehose, and Send Tweets in Under 5 Seconds
• Scaling Twitter: Making Twitter 10000 Percent Faster

dypsilon

Frontend Development

Attention: the list was moved to

https://github.com/dypsilon/frontend-dev-bookmarks

This page is not maintained anymore, please update your bookmarks.

---

pbailis

Context: I was asked for a list of interesting reading relating to "distributed databases, behavior under partitions and failures, failure detection." Here's what I came up with in about an hour.

For textbooks, "Introduction to Reliable and Secure Distributed Programming" is a superb introduction to distributed computing from a formal perspective; it's really not about "programming" or "engineering" but about distributed system fundamentals like consensus, distributed registers, and broadcast. Used in Berkeley's Distributed Computing course (and HT to @lalithsuresh) Book Site

Notes from courses like Lorenzo Alvisi's Distributed Computing class can be great.

There are a bunch of classics on causality, [Paxos](ht

jgrahamc

func worker(die chan bool) {
    for {
        select {
            // ... do stuff cases
        case <- die: 
            return
        }
    }
}