I recently found a nice emacs-mode, [irony-mode], which can be used with [company-mode], [flycheck-mode], and [eldoc-mode]. It works nicely with CMake-based projects. The document contains a list of instructions for setting things up. I assume that you're using a fresh-installed Ubuntu-12.04.5 (64-bit). It uses [Lean theorem prover][lean] as an example project.
;; Package | |
(require 'package) | |
(add-to-list 'package-archives | |
'("melpa" . "http://melpa.milkbox.net/packages/") t) | |
(package-initialize) | |
(package-refresh-contents) | |
;; Install required/optional packages for lean-mode | |
(defvar lean-mode-required-packages | |
'(company dash dash-functional flycheck whitespace-cleanup-mode |
A curated list by Eric Elliott and friends. Suggest links in the gist comments.
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This is a very exclusive collection of only must-have JavaScript links. I'm only listing my favorite links. Nothing else makes the cut. Feel free to suggest links if you think they're good enough to make this list. The really curious should feel free to browse the comments to find other links. I can't guarantee the quality of links in the comments.
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
# | |
# Copyright (c) 2015 Microsoft Corporation. All rights reserved. | |
# Released under Apache 2.0 license as described in the file LICENSE. | |
# | |
# Authors: Soonho Kong, Leonardo de Moura, Ulrik Buchholtz | |
# Python 2/3 compatibility | |
from __future__ import print_function |
\documentclass{article} | |
\usepackage{unixode} % Need to download from https://raw.githubusercontent.com/leanprover/tutorial/master/unixode.sty | |
\usepackage{minted} % Need to download from https://raw.githubusercontent.com/leanprover/tutorial/master/minted.sty | |
% Specify local pygments directory. Do the following in your working directory (where test.tex is located) | |
% hg clone https://bitbucket.org/leanprover/pygments-main && cd pygments-main && python setup.py build & cd .. | |
\renewcommand{\MintedPygmentize}{./pygments-main/pygmentize} | |
\setminted{encoding=utf-8} | |
\usepackage{fontspec} | |
\setmainfont{FreeSerif} | |
\setmonofont{FreeMono} |
// Toyota Powertrain Control Verification Benchmark: | |
// This is based on the following paper: | |
// | |
// Xiaoqing Jin, Jyotirmoy V. Deshmukh, James Kapinski, Koichi Ueda, and | |
// Ken Butts. 2014. Powertrain control verification benchmark. In | |
// Proceedings of the 17th international conference on Hybrid systems: | |
// computation and control (HSCC '14). ACM, New York, NY, USA, | |
// 253-262. DOI=http://dx.doi.org/10.1145/2562059.2562140 | |
// | |
// Originally written by Kyungmin Bae (kbae@cs.cmu.edu) |
#!/bin/bash | |
function benchmark_rev() { | |
REV=$1 | |
git clean -f &> /dev/null | |
git checkout $REV &> /dev/null | |
git clean -f &> /dev/null | |
if [ $? -ne 0 ]; then | |
echo "Checkout of $REV failed!" | |
exit 1 |
We want to integrate the probability density function for normal distribution:
To simplify the problem, let's pick mean = 0.0, standard deviation = 1.0. In theory, integration of this fuction from x = -oo to x = oo should give P = 1.0. Using CAPD, let's compute for the range X = [-10, 10] whose prob must be less than 1.0.