When you hear “Artificial Intelligence,” (AI) what do you think of?
A year ago, you may have pictured futuristic technology from sci-fi movies or humanoid robots.
Now, tools like ChatGPT or Google Bard most likely come to mind. AI technology is moving fast, and the landscape seems to change every day.
When it comes to software testing, AI can be implemented into your testing initiatives to increase efficiency. And while “AI in testing” is a buzz phrase that may prompt skepticism or concern, it can provide real value and streamline your testing efforts.
But what exactly is AI, where is it headed, and how can it optimize software testing? Keep reading to find out.
What is Artificial Intelligence?
Artificial Intelligence is a system with increasingly self-learning capabilities that can supplement human cognition and activities. It does this by understanding the environment, solving human problems, and performing human tasks.
For example, Google Maps uses AI to monitor traffic patterns and predict the best routes for you to take. Netflix uses machine learning (a subset of AI) to power its recommendation algorithm, which suggests shows suited to your preferences. ChatGPT is a generative AI chatbot tool using deep learning (a subset of machine learning) to generate humanlike responses to questions. It can be used in thousands of ways, and we’re only starting to discover how best to apply it and where its limitations are.
AI systems like these all operate by feeding data into intelligent algorithms that learn and improve by analyzing patterns within the data. And the more data these algorithms receive, the better they get at understanding the environment and predicting patterns. These systems also can be trained to perform both simple and complex tasks, depending on pattern matching algorithms.
Will AI Take Over Our Jobs?
There’s a looming fear AI will take over our jobs … and then the world. And while this makes for a great movie plot, the reality isn’t so scary. Human testing assisted by AI is still the best practice and will remain that way for the foreseeable future.
The VP of Product-Service Systems at EPAM, Tariq King, spoke about the future of AI at the 2022 STAREAST Software Testing conference. And while a lot has changed since then, his insights have only become more relevant.
As a pioneer in the AI space, King pinpointed our biggest problem as being an abundance of bad software people no longer trust. And with all this poorly produced software, there’s concern AI could be an efficient way to create more of it. But King went on to discuss a promising alternate reality: a world in which an abundance of good software is produced, and AI is kept stable by testers.
As the “AI revolution” gradually gains more traction, we can build higher-quality software and AI systems. Then use the AI technology to enable trusted software. And through all of this, a new subset of testers will emerge as the heroes who oversee and support these improved AI systems.
So, while testing practices are already beginning to shift, our world isn’t becoming a sci-fi movie just yet.
How AI Can Optimize Your Testing
Software testing has evolved rapidly in the past few decades. It began with manual testing, moved to early automated testing, agile testing, and then continuous testing. And now, it’s reached AI-augmented autonomous testing.
Achieving autonomous testing may seem like an impossible goal, but you can start implementing AI features that will create the foundation for it. AI can optimize your testing by accelerating test creation, expanding test coverage, and reducing test maintenance. But what does this look like? Let’s see some examples.
Object recognition is a form of intelligent design, which recognizes new objects and updates to add to the DOM without manual effort. There’s also framework generation which automatically scans your application to recommend a test framework.
Business process automation is an example of intelligent test execution, which helps to automate business workflows for end-to-end testing. Self-healing is also a form of intelligent test maintenance, which dynamically updates your test suite when your application changes or evolves.
Finally, AI-powered visual testing is newer form of test automation. It catches visual UI bugs like changes in color or font that other automated tests might miss. It does this by utilizing computer vision, which captures and interprets visual information from images or videos.
SmartBear Examples of AI in Testing
TestComplete, SmartBear’s UI test automation tool, has an AI-powered feature called the Intelligent Quality Add-on. It has intelligent capabilities such as self-healing tests, optical character recognition (OCR), and ML-based visual grid recognition.
These self-healing tests can automatically identify unexpected errors due to dynamic properties and recommend a better alternative. This prevents tests from failing, but more importantly, saves you time you would’ve spent reviewing these errors. OCR also helps you interact with content on complex applications by identifying objects based on text contents instead of their properties.
You also can be more efficient with ML-based visual grid recognition, which helps you validate data against complex objects like grids and tables. It does this by recognizing data within tables and verifying its contents against a baseline copy.
TestComplete also integrates with VisualTest, an automated visual testing tool. VisualTest leverages advanced AI to highlight visual changes in web applications. It takes screenshots, filters out expected changes and ignores false positives to speed up your flow. Then, you can automatically compare baseline images to spot and correct visual regressions.
In the future, SmartBear seeks to introduce an even higher level of AI to help you achieve autonomous testing. Our tools will one day use AI to generate test cases, run tests, and modify test cases (even if the UI changes), all without human involvement.
The Future Has Arrived
AI technology still has a ways to go, but it’s already making our lives easier from ChatGPT responses to software testing. And if we work to improve upon and utilize AI technology, things will only get better. Now, you can start to embrace AI and be the key to shaping the next phase of test automation.
Don’t let the future of testing pass you by. Start a free trial of any SmartBear UI test tool and begin leveraging AI.