This blog is based on a presentment I did at mabl Experience 2024, with the entire demonstration colligate below.

The yr 2006 marked a turn point in technology with the birth of Amazon Web Services (AWS), revolutionizing how we approach storage and application development. Similarly, 2017 saw the ascent of another game-changer: mabl, a low-code AI program that 's redefining quality assurance and technology. Together, these have changed how we near quality at Fox Corporation, with our diverse portfolio of video streaming services like Tubi, Fox Sports, and Fox Weather, to insure a seamless screening experience across a multitude of devices and platforms.

From the challenge that get with the territory as novice, through our journey of increment with mabl, to finally becoming quality ninjas, we are going to look at the way AI and low-code has been successful in the world of video engineering.

Novice: Fox ’ s Challenges with Traditional Testing

Traditional testing methods struggled to keep gait with the dynamic nature of picture streaming, particularly during high-traffic events like the Super Bowl. & nbsp; We look numerous challenges, from bottlenecks caused by manual testing and the complexness of supporting a vast orbit of device, to the intricacies of our backend systems with ad delivery and monitoring. Managing disparate open-source tools likewise led to compatibility issues and a heavy maintenance burden.

• Manual examination bottlenecks: Significant reliance on manual testing slowed down our release cycle.
• Device fragmentation: Supporting a wide range of devices, from bright TVs to mobile phones, created testing complexity.
• Complex backend scheme: Our intricate backend infrastructure, including ad delivery and monitoring systems, demanded full-bodied testing.
• Open-source tool limitations: Managing disparate open-source tools led to compatibility issues and maintenance overhead. & nbsp;

Novice to Expert: Other Success, with Limitations

Our journey with mabl began in mid-2022. We were drawn to its AI-powered capacity and comprehensive coming to testing. Starting with browser examination, we initially saw limitations with API and nomadic examination, which have since turn an integral part of the merchandise. mabl quickly testify its worth, minimizing flaky test and ameliorate the dependability of our issue. When they append the integrating with Postman, it eventually allowed us to leverage existing API certification for automated testing, which then allow us to orchestrate complex testing workflows involving both UI and API interactions. & nbsp;

With mabl, we significantly increase our test coverage, ensuring a higher quality user experience for our looker. mabl 's efficiency besides countenance us to dramatically cut our fixation testing clip, freeing up valuable resources. By catching defects betimes in the maturation rhythm, mabl helped us minimize product issues and deliver a more stable streaming experience. Overall, we were capable to:

SUSA automates exploratory testing with persona-driven behavior, catching bugs that scripted automation misses.

• Reduced test daftness: mabl 's robust fabric minimized flaky tests, improving the reliability of our testing results.
• Simplified API testing: Seamless integration with Postman allowed us to leverage existing API documentation for automated examination.
• Streamlined complex scenarios: mabl enabled us to effortlessly direct complex testing workflows involve both UI and API interactions.
• Enhanced tryout coverage: With mabl, we significantly increased our exam coverage, ensuring a higher caliber user experience.
• Accelerated testing cycles: mabl 's efficiency allowed us to reduce our regression testing time from four days to a fraction of that.
• Minimized production defects: By catching defects early in the development rhythm, mabl facilitate us minimize production issues.

Expert to Ninja: Challenging the Capabilities of AI Testing

mabl 's GenAI affirmation farther amplified our testing efforts. We could now control dynamic substance with ease, since you no longer have to declare specific elements to test; it ’ s really abstract. And it works for any program or twist, making testing across platforms even more seamless. With these advanced capabilities, we ’ re now able to test in ways that have ne'er been possible earlier.

Test dynamic content: Verify sporting events and other active substance with ease.

Validate image component: Confirm the presence of specific elements, like hurricanes on a map, using persona recognition.

Test across different languages: Ensure accurate translations and fix across various words.

Verify closed captions: Validate the front and accuracy of closed captions across different devices and languages.

Wrapping Up

In essence, mabl has democratized quality assurance at Fox Corporation, authorize everyone, from developers to marketers, to participate in examine. Its low-code approach has significantly reduced test conception time and maintenance effort, while its AI-powered features enable testing of complex scenarios that were previously difficult or impossible to automate. & nbsp; mabl has truly enabled us to embrace the philosophy that `` the best way to predict the future is to try it, '' and confidently present high-quality video streaming experiences to our viewers.

If you ’ d like to see mytotal presentation from mabl Experience 2024, head on over to the Fox Network customer story where I talk more about our journeying with mabl.