2:45 p.m. – 4:45 p.m. Wednesday 20th

Room D1+D2 - Track 7: Workshops

Audience

Testers, coders, people who need to supervise the building of systems made with AI help

Required

Laptop or competent tablet

Key-Learning

Specifying code behaviour with examples, in a short feedback process
Looking for expected and unexpected behaviours in AI-coded systems
An example of AI working in a red-green-refactor loop
How we went about finding out about this topic

Ask an AI to write code to pass your tests – then explore what's been delivered, and write more tests.

In this hands-on workshop, you’ll write tests, and an AI will write the code.

We’ll give you a zero-install environment with a simple unit testing framework, and an AI that can parse that framework. You’ll add to the tests, run the harness to see that they fail, then ask the AI to write code to make them pass. You’ll look at the code, ask for changes if it seems necessary, incorporate that code and run the tests for real. You’ll explore to find unexpected behaviours, and add tests to characterise those failures – or to expand what your system does. As you add more tests, the AI will make more code. Maybe you’ll pause to refactor the code within your tests.

Bart and James are exploring the different technologies and approaches that make this possible. We’ll bring worked examples, different test approaches, and enough experience (we hope) to help you to work towards insights that are relevant to you. All you need to bring are a laptop (or competent tablet) and an enquiring mind. You’ll take away direct experience of co-building code with an AI, and of finding problems in AI-coded systems. We hope that you’ll learn the power and the pitfalls of working in this way – and you'll see how we worked together to find out for ourselves.