LeventErkok

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-- A formalization of the Cheryl's birtday problem; using Haskell/SBV
--
-- See: http://www.nytimes.com/2015/04/15/science/a-math-problem-from-singapore-goes-viral-when-is-cheryls-birthday.html
--
-- By Levent Erkok, This file is in the public domain. Use it as you wish!
--
-- NB. Thanks to Amit Goel for suggesting the formalization strategy used in here.
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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?

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

david-christiansen

module FizzBuzzC

%default total

-- Dependently typed FizzBuzz, constructively

-- A number is fizzy if it is evenly divisible by 3
data Fizzy : Nat -> Type where
  ZeroFizzy : Fizzy 0
  Fizz : Fizzy n -> Fizzy (3 + n)

michaelochurch

Real estate (like oil in the short term, cf. "oil shocks" of the 1970s) is extremely supply-inelastic, 
such that a 1% loss of supply might cause prices to go up *a lot* more than 1%-- possibly 10%, 20%, 
even 2x. The result of this is that a destruction of real estate supply will actually increase the 
*total* market value: a cataclysmic loss of 5% of NYC's real estate would drive prices through the roof 
and make the price level look "healthy" (from the buyer-centric perspective common in the US when it 
comes to housing). But no value was created! Much was destroyed. 

The 2000s run-up in NYC's housing costs was driven largely by speculation after 9/11. While we 
*actually* had 12+ subsequent years with no major domestic terror attacks, there were a large number of 
(esp. foreign) speculators who expected future attacks in major cities and bought lots of RE in 

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

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/

NathanHowell

{-# OPTIONS_GHC -fno-warn-orphans #-}
{-# LANGUAGE BangPatterns #-}
{-# LANGUAGE DeriveFunctor #-}
{-# LANGUAGE DeriveFoldable #-}
{-# LANGUAGE DeriveTraversable #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE GeneralizedNewtypeDeriving #-}
{-# LANGUAGE NamedFieldPuns #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE StandaloneDeriving #-}

romainguinot

--- checkgmail	2013-02-28 14:24:44.614055113 +0100
+++ checkgmail.current	2013-03-01 22:22:30.211693526 +0100
@@ -33,13 +33,18 @@
 
 # global variables (can't be set global in the BEGIN block)
 my ($version, $silent, $nocrypt, $update, $notsexy, $profile, $disable_monitors_check, 
-		$private, $cookies, $popup_size, $hosted_tmp, $show_popup_delay, 
-		$popup_persistence, $usekwallet, $libsexy, $nologin, $mailno, $debug);
+		$private, $cookies, $two_factor_auth_switch, $popup_size, $hosted_tmp, $show_popup_delay,
+		$popup_persistence, $use_kwallet, $libsexy, $nologin, $mailno, $debug);

swannodette

;; list comprehensions are often used as a poor man's Prolog
;; consider the following, it has only one solution 
;; [1 1 1 1 1 1 1 1 1 1] yet we actually consider 10^10 possibilities

(for [a (range 1 11)
      b (range 1 11)
      c (range 1 11)
      d (range 1 11)
      e (range 1 11)
      f (range 1 11)