There’s no denying that artificial intelligence is the hottest thing in tech right now. It’s in everything, including your phone. It’s not surprising, then, that programmers are using it to improve automation testing. How does it work, and why should you implement it? Here’s what you should know 💡
How Artificial Intelligence Works In Automation Testing
Very simply put, AI uses machine learning in order to generate results. It uses these algorithms to make trained models and uses these models to make predictions. This is an oversimplification of the process, but it’s one that most AI models use.
Right now, it’s not that clear whether AI will bring better results when you use it for test automation. There’s a lot of potential there, but it’s not quite at the point where it’s more accurate than current methods. Even so, it brings a lot of benefits that you should look into 🔎
How Machine Learning Produces Test Results
If you’re going to use AI in automated testing, you need to know how it produces results. There are three different ways it can do this:
- Training: When you start using AI, you’ll need to train it to look for a specific dataset. That includes the codebase, application interface, logs, test cases, and so on. This needs to be detailed, as if you don’t have enough info you won’t get the best results.
- Result generation: At this point, your AI model will create test cases. It will check the test cases for code coverage, accuracy, and perform tests on them. A tester will need to check these cases, and ensure that they’re useable.
- Improvement: As the company uses the AI model, it will continue to improve as it’s used. It will learn from every case it processes, and so you’ll get better results each time.
AI And Its Uses In Automation Testing
That’s a simplified way of looking at how AI works. How can it be applied to test automation in your case? 🤔 There are a few different ways you can use it, including the following:
Creating Unit Tests: Unit testing is highly time-consuming, and that’s why a lot of companies are making the switch to using AI to do this. ‘AI is highly useful if you’re going to introduce testing late in the product’s life cycle’ says tech blogger Alan Croft. ‘It helps save a lot of time and manpower’.
These test units can be generated very quickly, which makes them quicker to use. However, the AI-generated test units just mirror the code on which they’re built, so they cannot actually interpret the functionality that the code should have. In that way, they are somewhat limited.
Automated User Interface Testing: This is where most developers will use artificial intelligence testing. AI can navigate through a UI, verifying objects and delivering data on how it works.
It’s commonly used as even minor issues with the UI don’t cause the AI to fail in testing. It also gives you increased code coverage. However, it can be somewhat limited as there are so many modern UIs available, so right now it’s not as effective as it could be. There could well be improvements in the future, though.
API Testing Using AI: API testing is a serious undertaking, needing you to understand the API and set up multiple tests for multiple scenarios. ‘AI helps you streamline this process, which saves a lot of time’ says business writer Sasha Hilton. ‘That’s incredibly valuable when you need to get a product out the door’.
This is something that has become invaluable for novice testers. It allows them to get a product ready sooner. Change management is easier too, as some of it can be handled by the AI itself. However, it can be difficult to set up, so you’ll need someone with experience to handle this.
Maintaining Automation Testing with Artificial Intelligence
One of the best things about AI testing is that it can evaluate changes to the code. This shouldn’t cause problems with the test suite, and in fact, makes it easier to do updates ✅ When it evaluates the code, it can fix existing tests with updates to UI elements, names, and so on.
Generating AI-Based Test Data
This is where AI testing is creating the best value for developers. A good AI test suite will be able to generate data sets that can be used for testing. This includes things like info like age and weight or profile pictures. With that data, you can get the AI to learn more and give more consistent results.
Conclusion
As you can see, artificial intelligence and machine learning are becoming valuable tools in testing 🔨 They’re not perfect yet, but the tech is developing all the time, so you should check it out!