That’s a wrap on this year’s STARWEST conference!
The main theme of this year’s conference largely centered around the ways in which AI continues to alleviate pain points for testers and how to incorporate AI into your testing processes going forward to accelerate growth.
In our preview blog, we highlighted our session on leveraging AI in continuous testing. In this blog, we will provide a recap of that session as well as delve into the key insights and takeaways from the conference.
Time to dive in!
Related Reading: The Future Is Now: Mobile & Web Application Testing With AI
Session Recap: Achieving Smarter Testing: Leveraging AI in Continuous Testing
Perforce’s speaking session, led by Stephen Feloney, Vice President of Continuous Testing Products, explored AI’s current and future role in testing, how to implement AI intentionally for high-value results, potential challenges of AI in testing, how to harness generative AI to create reliable synthetic test data, and more.
In the session, attendees learned about:
- AI's Role in Testing: AI is transforming testing across functional, performance, and security testing, with generative AI now playing a pivotal role in automation and analysis.
- Focus on High-Value AI Implementation: Companies should avoid using AI just for the sake of it. Instead, focus on areas where AI can deliver the most value, such as analysis, test data management, and maintenance.
- AI-Driven Test Analysis: AI simplifies analyzing large sets of test results, helping testers quickly pinpoint issues such as network problems, UI changes, or faulty APIs.
- AI for Test Data: AI-generated synthetic data is critical for creating negative test cases, synchronizing data across systems, and improving test accuracy, reducing the dependency on production data.
- Automated Test Creation and Maintenance: AI will increasingly automate test generation and maintenance, eliminating the need for traditional frameworks like Selenium or Cypress.
- Challenges with AI: Governance and trust in AI-generated results are key challenges. Companies need to ensure they can govern and maintain control over AI outputs.
- Future of Testing with AI: Over the next 1-2 years, automated and AI-driven testing will become more prevalent, drastically improving efficiency and reducing reliance on regression suites.
Key Themes of STARWEST 2024
The name of the game this year is AI. In many of the speaking sessions, discussion centered around harnessing the power of AI to streamline testing and enhance developer productivity.
Below, we will touch on some key takeaways from the conference related to AI in testing.
Cultivating Trust in AI Should Be Prioritized
While AI is undoubtedly here to stay and is only growing in prominence every day, many teams are still experiencing hesitation around its security.
For organizations, especially large enterprises, protecting data is paramount. Faulty cybersecurity can lead to financial setbacks and loss of reputation—something enterprises cannot risk.
Both Perfecto and BlazeMeter are committed to prioritizing data security to ensure both compliance and privacy. Perfecto’s world-class device cloud is fast, secure, comprehensive, and self-healing. BlazeMeter’s Test Data Pro optimizes test data generation, addressing common AI implementation challenges by providing reliable and usable test data, vastly expanded test coverage, increased and reliable accuracy, speed of testing, and bolstered app resilience. This AI-driven data helps solve the problem teams often face of acquiring usable and reliable test data. Test Data Pro assists with security by preventing customers from using real data instead of synthetic data.
Related Reading: BlazeMeter Test Data Pro: AI-Driven Test Data Generation & Beyond
AI in Testing Is the Most Frequent Use Case
In Perfecto and BlazeMeter’s 2024 State of Continuous Testing Report, 48% of respondents indicated they are interested in AI but have not yet started any initiatives, while only 11% are already implementing AI techniques. Research from EY supports these findings, noting that despite AI’s low barrier to entry, “AI isn’t yet a mainstream part of enterprise testing, but if you wait too long, you’ll fall behind.”
Get more insights into the future of testing with AI in Perfecto’s eBook, ‘The Future Is Now: Mobile & Web Application Testing With AI.’
One of the many benefits of AI is that it enables faster and smarter test creation by generating scripts instantly, so teams no longer rely on manual or hybrid coding. AI can also assist by generating reliable test data—which is often a pain point for testers.
Related Viewing: The Future of Testing: A Conversation About the Use of AI and ML
Developers Will Benefit the Most from Generative AI
Generative AI—or AI that uses machine learning to create new content on the fly, including text, images, and other data—is poised to unleash a host of benefits to application developers.
Using generative AI will not only increase speed and efficiency of application development, but it will enable teams to test more complex use cases faster—thereby increasing developer productivity.
In a recent report from McKinsey & Company on the economic potential of generative AI, it was stated that “Generative AI’s impact on productivity could add trillions of dollars in value to the global economy.”
Continuing to embrace generative AI tools while moving from manual to automated testing will set your team up for success going forward.
Related Reading: The Future of Testing Innovation With Perfecto
Perfecto’s AI-Powered Intelligent Testing Features & Capabilities
At Perfecto, we believe AI is the future of testing. We continually innovate to stay at the forefront of technological advancements, ensuring our customers enjoy a seamless, cutting-edge testing experience.
Our comprehensive testing platform is supported by the following AI features and capabilities:
AI-Powered Root Cause Analysis
With Perfecto’s AI-powered Root Cause Analysis, teams can quickly pinpoint the true causes of test failures, significantly reducing time and effort spent on troubleshooting.
Harness the power of Perfecto’s AI-Powered Root Cause Analysis, which includes the following key features:
- Smarter Failure Reasons: AI identifies real failure reasons and groups similar causes for easier resolution.
- “Failed vs. Last Good” Execution Comparisons: Automatically highlights differences between failed and successful executions.
- Backend Root Cause Identification: Analyzes API call traces to find backend-related test failures.
- Test Failure Impact Analysis: Prioritizes the most critical failures and suggests corrective steps.
AI-Driven Test Execution and Validation
AI-Driven Testing empowers testers to define validation conditions and execute tests using everyday language, eliminating the need for complex scripting.
Components:
- AI-Driven Validation: Use plain language to define test success criteria.
- AI Execution: Create and run tests based on natural language specifications. This approach surpasses traditional script-based testing, allowing direct testing based on requirements and test plans.
AI-Driven Image Data Generation
When performing tests that require the uploading of images (such as checks, paystubs, and other documents containing sensitive user data), testers will now be able to automatically generate these images on the fly. In the same way that AI facilitates the generations of usable test data, it will now generate images based on tester specs, complete with usable data like account numbers.
AI-Driven Image Data Generation will save testing teams the hassle of having to create usable test images. Instead, they can generate these images as they go, without having to stop the testing process.
Pop-Up Detection
Pop-Up Detection utilizes a trained ML model to detect if there is a pop-up displayed on screen during a test. Pop-ups typically cause tests to fail, as the pop-up blocks the expected flow of the test. With Perfecto’s Pop-Up Detection, AI will recognize when the test was stuck due to a pop-up.
Self-Healing Object Identification
Self-Healing Object Identification locates elements on screen during a test, such as menus, buttons, and text fields. Perfecto’s self-healing AI component learns over time which location for these objects on the screen are the most efficient and resilient during a test—ensuring that Perfecto tests can locate the right object on the page despite changes made to the page layout and structure.
BlazeMeter Test Data Pro
Every software test needs data—and you’ve never experienced test data like this. With AI-powered Test Data Pro, teams can transform their testing through optimized AI test data generation, vastly expanded test coverage, increased and reliable accuracy, and bolstered resilience of your app. Accelerate testing and elevating application quality just got easier.
Related Reading: Your Guide to Root Cause Analysis Tools & Techniques
Bottom Line
Whether you attended the 2024 STARWEST conference in person or virtually, we hope you took away valuable insights about the future of AI in testing and more.
Perfecto is continually innovating to remain in step with developments in technology and new releases to ensure a seamless testing experience for customers while staying ahead of market trends.
When you partner with Perfecto, you will experience When you embrace the power of AI, your team will experience the following benefits:
- Increase operational efficiency
- Eliminate script dependency
- Streamline testing with generative data & images
- Ensure smooth test execution
- Ensure robust & reliable tests
- Reliable test data on demand
Harness the power of AI by signing up for a free 14-day trial of Perfecto today.