Zac Hatfield-Dodds Zac-HD

## projects.md

      
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    EA Hackathon Projects

Almost all projects started at hackathons die young, whether because the team doesn't prioritize continuing work,
or because the idea wasn't actually what users needed.  So: if you want impact, I think you should contribute to
existing projects such as the open-source issues below.
Contributing to open-source is also a great way to develop software engineering skills, which are a
key bottleneck for AI Safety research
among other fields, and I think a day modelled on PyCon sprints can help.
I've selected the issues below to be feasible first-time contributions to open source for people who are already comfortable programming in Python. Even if they seem sm

  
## student-project-ideas.md

      
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                Undergraduate project ideas for PBT research
              
          
    Property-Based Testing Projects for Undergraduate Researchers

Hypothesis is an advanced and
widely-used property-based testing
framework, used by thousands of companies and open source projects.
Until moving to Anthropic in 2021,
Zac Hatfield-Dodds supervised related
research projects for students
interested in advanced testing and verification. All projects require

  
## .github__workflows__ci.yml
name: Project CI

on:
  push:
    branches: [ master ]
  pull_request:
    branches: [ master ]

jobs:
  run-tox:

## budget.py
"""
You are writing simple budgeting softare. A Budget consists of a total limit,
represented as a positive integer, and a dictionary of category limits,
represented as a map from strings to integers. For example:

    {
        "total_limit": 50,
        "category_limits": {
            "food": 10,
            "rent": 11,

## hypothesis-crosshair.md

      
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                Notes for a project to combine property-based tests with SAT-solving, based on the Hypothesis and Crosshair libraries.
              
          
    Hybrid concrete/symbolic testing

You’ve probably heard that "testing can be used to show the presence of bugs,
but never to show their absence" - usually as an argument for formal methods
like symbolic execution. On the other hand, testing is often easier and
finds bugs in formally verified systems too.
But why not use both?
Crosshair is an SMT-based symbolic
execution tool for Python. Providing an interface or extension to check Hypothesis

  
## demo.py
# Some example code for PyH2 hardware testing

import math
import os
import random
import sys

import afl

from hypothesis import given, strategies as st

## plyfile-test.py
import string

from hypothesis import given, strategies as st
from hypothesis.extra.numpy import arrays

#import os, sys; sys.path.insert(0, os.path.abspath('.')); del sys; del os
import plyfile

# Simple strategy for a list of unicode strings
st_comments = st.lists(elements=st.text())
	name: Project CI

	on:
	push:
	branches: [ master ]
	pull_request:
	branches: [ master ]

	jobs:
	run-tox:
	"""
	You are writing simple budgeting softare. A Budget consists of a total limit,
	represented as a positive integer, and a dictionary of category limits,
	represented as a map from strings to integers. For example:

	{
	"total_limit": 50,
	"category_limits": {
	"food": 10,
	"rent": 11,
	# Some example code for PyH2 hardware testing

	import math
	import os
	import random
	import sys

	import afl

	from hypothesis import given, strategies as st
	import string

	from hypothesis import given, strategies as st
	from hypothesis.extra.numpy import arrays

	#import os, sys; sys.path.insert(0, os.path.abspath('.')); del sys; del os
	import plyfile

	# Simple strategy for a list of unicode strings
	st_comments = st.lists(elements=st.text())