octocat

# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so

# Packages #

monperrus

import java.io.*;
import java.util.*;

/** The class encapsulates an implementation of the Apriori algorithm
 * to compute frequent itemsets.
 * 
 * Datasets contains integers (>=0) separated by spaces, one transaction by line, e.g.
 * 1 2 3
 * 0 9
 * 1 9

EvanHahn

// Start Express
const express = require("express");
const app = express();

// Set the view directory to /views
app.set("views", __dirname + "/views");

// Let's use the Pug templating language
app.set("view engine", "pug");

ndarville

[Isolating Differences Between Files][paper]

Advantage over Other Algorithms

The diff output is more specific:

[I]f a whole block of text is moved, then all of it, rather than just the beginning and end, is detected as changed.

>The algorithm described here avoids these difficulties. It detects differences that correspond very closely to our intuitive notion of difference.

hellerbarde

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             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs