Eggplant AI 2.0 Bringing Machine Learning to Software Testing
- By Richard Seeley
If you ever handwrote a test script for an application you would probably agree that it is not a very fun task.
Nor is it very effective.
"Comprehensively testing an app is an impossibly large task," opines Testplant, a digital automation intelligence company, in a statement few if any folks who toil in QA would argue with. "There are an infinite number of ways a user can navigate through any application, which is why test teams cover less than 1 percent of the possible user journeys in their testing, and why all apps have defects."
Since at least the 1980s, there have been tools to help facilitate test script development and then repeatedly run that script to see if it can break the application. That was back in the days of waterfall development when application testing was a relatively more leisurely occupation than it is in the era of DevOps and mobile can-you-have-it-for-me-yesterday apps.
But Testplant, based in Boulder, Colo., and London, is aiming to disrupt software testing by bringing artificial intelligence to the thankless task.
This week the company announced the availability of the latest version of its whimsically named Eggplant AI product.
"Eggplant AI 2.0 uses AI, machine learning, and analytics to intelligently navigate applications, predict where quality issues are most likely to occur, and correlate data to help product teams quickly identify and resolve issues," according to the Testplant press release. According to the vendor, Eggplant AI 2.0:
- Uses AI and neural networks to auto-generate tests and focus test execution on the user journeys most likely to find defects
- Enables software and app vendors to keep up with the pace of DevOps and user expectations
- Helps improve the user experience
"Eggplant AI 2.0 is a huge leap forward in the evolution of test automation," Antony Edwards, CTO, Testplant, is quoted as saying in the press announcement. He added: "This is the future of testing and is the only way software and app vendors are going to keep up with the demands of users and the pace of DevOps."
Testplant says its AI approach to testing makes use of machine learning algorithms to find patterns that can identify software defects. It then auto-generates tests to follow likely "user journeys" through an app to uncover potential problems.
"This significantly increases the effectiveness and efficiency of testing," the company announcement says, "delivering real improvements to the app that users notice."
Testing with Eggplant AI 2.0 can also integrate an organization's standard tests with those developed via machine learning, Testplant says. For test teams that are required to run "smoke tests" to cover things they always look for in an app regardless of the likelihood that a problem may exist, Eggplant AI 2.0 is designed to make it easy to include those basic test scenarios into the testing.
Eggplant AI 2.0 is part of Testplant's Digital Automation Intelligence Suite, which also includes Eggplant Manager for orchestrating test execution, Eggplant Automation Cloud to manage hosted test devices, and Eggplant Integrations to integrate with an organization's DevOps infrastructure, the company announcement explained.