Frank-Buss

# run like this:
# julia -O3 --check-bounds=no tm.jl busy-beaver-5.json --fast
using ArgParse
using JSON

# ANSI codes for inverse video and reset
const INVERSE = "\u001B[7m"
const RESET = "\u001B[0m"

function parse_commandline()

Frank-Buss

First add this to your CMakeLists.txt file:

if(BOARD STREQUAL "native_posix_64")
  target_compile_options(app PRIVATE -fsanitize=address -fsanitize=undefined)
  target_link_options(app PRIVATE -fsanitize=address -fsanitize=undefined)
  target_link_libraries(app PRIVATE asan ubsan)
endif()

For testing I used the blinky example, and added this at the beginning of the main function:

Frank-Buss

frank@wopr:~/tmp$ cat overflow.c 
#include <assert.h>
#include <stdio.h>

int foo(int a) {
  assert(a+100 > a);
  printf("%d %d\n",a+100,a);
  return a;
}

Frank-Buss

#!/usr/bin/env python3

import requests
response = requests.get("https://httpbin.org/ip")
data = response.json()
ip = data.get("origin", "Unknown")
print(f"Your IP address is: {ip}")

Frank-Buss

import re
import sys

# List of valid TLDs (this is a small subset, you may want to use a more comprehensive list)
VALID_TLDS = set(['com', 'org', 'net', 'edu', 'gov', 'io', 'co', 'uk', 'de', 'fr', 'jp', 'cn', 'au', 'us'])

def is_valid_domain(domain):
    pattern = r'^[a-zA-Z0-9]([a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?(\.[a-zA-Z]{2,})+$'
    if not re.match(pattern, domain):
        return False

Frank-Buss

# create a new private key
frank@hal9000:~/tmp$ openssl genpkey -algorithm RSA -out private_key.pem -pkeyopt rsa_keygen_bits:2048
..+.+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*.+.........+.+..+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*.....+..+...+....+......+..+...+.......+..+....+..+...+....+..+......+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
.+..+.........+......+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*......+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*.....+.........+....+.....+..........+..+.........+....+..+............+.+..+.......+.....+.+...............+..+............+...+...+.+......+............+...............+..+.............+........+...+......+....+......+........+...+..........+............+..+....+..+...+....+..+....+......+.....+...+.+.....+................+.......................+.+.........+...........+.+...+..+.............+......+..............+...+....+........+.+..+.....

Frank-Buss

#!/usr/bin/env python3

# automatically pins all your workflows, see
# https://github.com/fmtlib/fmt/issues/3449
# for details

import sys
import requests
import os

Frank-Buss

# Audio loudness calculation and normalization.
# The LUFS calculations here are all based on:
# ITU documentation: https://www.itu.int/dms_pubrec/itu-r/rec/bs/R-REC-BS.1770-4-201510-I!!PDF-E.pdf
# EBU documentation: https://tech.ebu.ch/docs/tech/tech3341.pdf
# pyloudnorm by csteinmetz1: https://github.com/csteinmetz1/pyloudnorm
# loudness.py by BrechtDeMan: https://github.com/BrechtDeMan/loudness.py
# Special thanks to these authors!
# I just rewrote some codes to enable short-term and momentary loudness calculations and normalizations for more convinent batch processing of audio files.

import numpy as np

Frank-Buss

#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>

#define PLAYERS 5

uint8_t pos[PLAYERS];

int random2to12() {
    return (rand() % 11) + 2;

Frank-Buss

#!/usr/bin/env python3
#
# Test script for the uncensored WizardLM model:
# https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGML
# 
# Tested on Mac Mini M1, with 16 GB RAM. Needs some libraries:
#
# pip install torch transformers accelerate bitsandbytes
# CT_METAL=1 pip install ctransformers --no-binary ctransformers
#