Software Testing: Is AI in Your Future?
I am always looking to see what the next big trend in tech will be.
Some of the recent trends include Agile, DevOps, and Internet of Things (IoT). Now the new trend appears to be artificial intelligence (AI).
In 2017, Tech Giants such as Amazon, Facebook, Google, and Microsoft spent billions on AI and machine learning initiatives. At Build 2017, Microsoft announced Microsoft Cognitive Services to help developers integrate AI into the applications they are developing.
It looks like AI is just going to keep growing. And there is clearly a role for it to play in software testing, too.
Tools Will Need to Evolve or Die
Software development — and software testing — continues to evolve in step with the adoption of Agile and DevOps methodologies. And software development will continue to evolve in the era of AI, too.
AI and machine learning are centered on training software to understand input data versus output today. This is very similar to the testing activities performed manually today. We type an input into a field, and we look for an expected output.
With AI, the machine does the testing instead. It comes up with many more variations of the test. It automatically runs many more tests than a human could supervise. And it even handles changes to the code and UI that previously had to be made by QA professionals. Some examples of this are adding fields or changing the inputs and anticipating outputs.
Even without AI, testing tools have evolved. Today’s tools help testers create, organize, and prioritize test cases. Efficiently managing tests and their outcomes, as well as remediating defects, remains essential to giving the developers the feedback they need.
Here are two things to consider when it comes to software testing tools (with or without AI):
Testing data is growing. And spreadsheets alone can’t report on trends in test data or quickly rerun tests. Your organizations need more from testing.
Test management tools need to evolve for scalability. Testers should be able to use these tools to support quick test reruns or Nth number of test cases.
Product development phases are no longer isolated. Today, each phase of product development is an integral part of the development lifecycle.
Application lifecycle management tools need to support the entire development process. That means gathering requirements, managing tests, and performing traceability.
Testers Will Become Extinct
AI is going to replace testers as we know them today. Instead of being a QA team, software testers will be a test automation team.
That’s because AI is going to make testing more efficient. Test automation engineers will be the subject matter experts teaching AI to execute the tests— and many more tests and permutations — faster than they could do manually.
Humans will supervise the outcome of the test, adding the critical human element. After all, there are three types of requirements for testing (implicit, explicit, and latent). But only explicit testing can be done by AI.
“A lot of things are going to change in the testing field with the entry of AI. Almost 70 percent of testing is repetitive and AI can quickly occupy that space. The 30 percent left is questioning the system, and that’s what testers need to focus on. AI is the next big thing in testing, but it won’t replace humans. The testers working alongside AI can quickly revolutionize the way we test today.” — Vijay Shinde, Founder of Software Testing Help
Testing Always Changes
You’d be hard-pressed to find any software QA professional who would say testing is the same today as it was five years ago.
And similarly, AI is going to play an important role in the future of software testing. But it’s not going to change software testing overnight. And there are fundamental ideas about testing and quality that will remain (and that only humans can understand) for the foreseeable future.
Learn more about the impact of AI on software testing. Join us for a webinar on Thursday, February 22: "3 Ways AI Will Change Software Testing."