steipete

	_viewControllerFlags (struct ?): {
		appearState (b2): 0
		isEditing (b1): NO
		isPerformingModalTransition (b1): NO
		hidesBottomBarWhenPushed (b1): NO
		autoresizesArchivedViewToFullSize (b1): NO
		viewLoadedFromControllerNib (b1): NO
		isRootViewController (b1): NO
		customizesForPresentationInPopover (b1): NO
		isSuspended (b1): NO

andymatuschak

A composable pattern for pure state machines with effects

State machines are everywhere in interactive systems, but they're rarely defined clearly and explicitly. Given some big blob of code including implicit state machines, which transitions are possible and under what conditions? What effects take place on what transitions?

There are existing design patterns for state machines, but all the patterns I've seen complect side effects with the structure of the state machine itself. Instances of these patterns are difficult to test without mocking, and they end up with more dependencies. Worse, the classic patterns compose poorly: hierarchical state machines are typically not straightforward extensions. The functional programming world has solutions, but they don't transpose neatly enough to be broadly usable in mainstream languages.

Here I present a composable pattern for pure state machiness with effects,

keyboardr

#if (${PACKAGE_NAME} && ${PACKAGE_NAME} != "")package ${PACKAGE_NAME};#end

import android.app.Activity;
import android.app.Fragment;
import android.app.FragmentManager;

#parse("File Header.java")
public class ${NAME} extends Fragment {
    
  private static final String FRAG_TAG = ${NAME}.class.getCanonicalName();

tel

{-# LANGUAGE RankNTypes #-}
{-# LANGUAGE TypeOperators #-}
{-# LANGUAGE GADTs #-}
{-# LANGUAGE DeriveFunctor #-}

module Tesser where

import Data.List (foldl')
import Data.Profunctor
import Data.Bifunctor

chrisdone

Typing Haskell in Haskell

MARK P. JONES

Pacific Software Research Center

Department of Computer Science and Engineering

Oregon Graduate Institute of Science and Technology

mchambers

// Here we'll use Swift's IDE-supporting reflect()
// function to build a basic JSON serializer.

// Per the fine engineers at WWDC, Swift's reflection support
// exists purely to support the IDE and the Playground. But
// we can have some fun with it anyway. ;)

class SerializerBase {
}

nelsnelson

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Syscall on Intel 5150 ...................... 105 ns
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Context switch on Intel 5150 ............. 4,300 ns  =   4 µs

Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs

max-mapper

Your API does REST, but can it SLEEP?

SLEEP (Syncable Lightweight Event Emitting Persistence) is an emerging standard for distributed data sync using HTTP and JSON. A generalized version of CouchDB's much lauded built-in replication, SLEEP extends the REST architecture to define a way in which databases can offer syncable JSON APIs that foster open data innovation by allowing developers to replicate entire databases over the net.

---

SLEEP comes from the Apache CouchDB project which is now widely known for it's multi-master streaming HTTP + JSON replication. This is possible in part because of the CouchDB _changes feed, which is a particular API that lets you see if there have been any changes made to the database since last time you synchronized. CouchDB can efficiently implement the _changes feed because of one subtle difference between it and most other databases: it stores a history of all changes that happen to the database, including deletes.

If you synchronize data from a remote source and then the