Introduction
TestDriver is a next generation autonomous AI agent for end-to-end testing of web & desktop
TestDriver isn't like any test framework you've used before - it's more like your own QA employee with their own development environment.
Tell TestDriver what to do in natural language
TestDriver looks at the screen and uses mouse and keyboard emulation to accomplish the goal
TestDriver is black-box testing. It doesn't use selectors or static analysis.
Advantages
TestDriver then uses AI vision and hardware emulation to simulate real user on their own computer. This has three main advantages:
Easier set up: No need to add test IDs or craft complex selectors
Less Maintenance: Tests don't break when code changes
More Power: TestDriver can test any application and control any OS setting
Just tell TestDriver what to do
Use our CLI to tell TestDriver what to do, like so:
Possibilities
As you can imagine, a specialized QA agent with it's own computer is extremely powerful. TestDriver can:
Test any user flow on any website in any browser
Clone, build, and test any desktop app
Render multiple browser windows and popups like 3rd party auth
Test
<canvas>
,<iframe>
, and<video>
tags with easeUse file selectors to upload files to the browser
Resize the browser
Test chrome extensions
Test integrations between applications
The problem with current approach to end-to-end testing
End-to-end is commonly described as the most expensive and time-consuming test method. Right now we write end-to-end tests using complex selectors that are tightly coupled with the code.
You've probably seen selectors like this:
This tight coupling means developers need to spend time to understand the codebase and maintain the tests every time the code changes. And code is always changing!
End-to-end is about users, not code
In end-to-end testing the business priority is usability. All that really matters is that the user can accomplish the goal.
TestDriver uses human language to define test requirements. Then our simulated software tester figures out how to accomplish those goals.
These high level instructions are easier to create and maintain because they are loosely coupled from the codebase. We're describing a high level goal, not a low level interaction.
The tests will still continue to work even when the junior developer changes .product-card
to .product.card
or the designers change Add to Cart
to Buy Now
. The concepts remain the same so the AI will adapt.
How exactly does this work?
TestDriver's AI is a fine tuned model developed over the course of more than a year with the help of computer vision experts, custom research tooling, and a few million dollars in funding (thanks VCs).
TestDriver uses a combination of reinforcement learning and computer vision. The context from successful text executions inform future executions. Here's an example of the context our model considers when locating a text match:
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