mbinna

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

thesamesam

FAQ on the xz-utils backdoor (CVE-2024-3094)

This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.

Background

On March 29th, 2024, a backdoor was discovered in xz-utils, a suite of software that

Mefistophell

Question: I want to compile my Rust source code for the Windows platform but I use macOS.

Solution:

1. Install target mingw-w64: brew install mingw-w64
2. Add target to rustup: rustup target add x86_64-pc-windows-gnu
3. Create .cargo/config
4. Add the instructions below to .cargo/config

[target.x86_64-pc-windows-gnu]

brendanzab

NOTE: This was first authored on 26 Feb 2014. Things may have changed since then.

C++'s Templates

C++'s templates could be seen as forming a duck typed, purely functional code generation program that is run at compile time. Types are not checked at the initial invocation stage, rather the template continues to expand until it is either successful, or runs into an operation that is not supported by that specific type – in that case the compiler spits out a 'stack trace' of the state of the template expansion.

To see this in action, lets look at a very simple example:

template 

pervognsen

Multi-dimensional array views for systems programmers

As C programmers, most of us think of pointer arithmetic for multi-dimensional arrays in a nested way:

The address for a 1-dimensional array is base + x. The address for a 2-dimensional array is base + x + y*x_size for row-major layout and base + y + x*y_size for column-major layout. The address for a 3-dimensional array is base + x + (y + z*y_size)*x_size for row-column-major layout. And so on.

marcan

#!/usr/bin/python3
#
# Simple Bloom filter implementation in Python 3
# Copyright 2017 Hector Martin "marcan" <marcan@marcan.st>
# Licensed under the terms of the MIT license
#
# Written to be used with the Have I been pwned? password list:
#   https://haveibeenpwned.com/passwords
#
# Download the pre-computed filter here (968MB, k=11, false positive p=0.0005):

mmozeiko

//

struct TerminalCell
{
    // cell index into GlyphTexture, should be two 16-bit (x,y) values packed: "x | (y << 16)"
    uint GlyphIndex;

    // 0xAABBGGRR encoded colors, nonzero alpha for Foreground indicates to render colored-glyph
    // which means use RGB values from GlyphTexture directly as output, not as  ClearType blending weights
    uint Foreground;

williballenthin

import os
import sys
import logging

import pefile
import ucutils
import unicorn
import capstone
import argparse

pervognsen

A quadratic space is a real vector space V with a quadratic form Q(x), e.g. V = R^n with Q as the squared length. The Clifford algebra Cl(V) of a quadratic space is the associative algebra that contains V and satisfies x^2 = Q(x) for all x in V. We're imposing by fiat that the square of a vector should be the quadratic form's value and seeing where it takes us. Treat x^2 = Q(x) as a symbolic rewriting rule that lets you replace x^2 or x x with Q(x) and vice versa whenever x is a vector. Beyond that Cl(V) satisfies the standard axioms of an algebra: it lets you multiply by scalars, it's associative and distributive, but not necessarily commutative.

Remarkably, this is all you need to derive everything about Clifford algebras.

Let me show you how easy it is to bootstrap the theory from nothing.

We know Cl(V) contains a copy of V. Since x^2 = Q(x) for all x, it must also contain a copy of some nonnegative reals.

alvinhochun

Control Flow Guard (CFG/CFGuard) for mingw-w64

Control Flow Guard is a security mitigation that verifies the target address of indirect calls. It works by having the compiler insert a check at indirect call sites to verify the validity of the call target, and also the linker write the necessary data and flags into the PE/COFF image to enable the feature on Windows' end.