Cheat Sheet: Test More & Script Less

Demand is higher than ever for rapid, reliable, and comprehensive software testing. That is driving the quest for innovative approaches that streamline testing processes while ensuring high-quality results. Enter GenAI-driven testing, a revolutionary advance that changes the game by allowing you to “Test More and Script Less.”

With Appvance’s GenAI-driven platform AIQ in mind, this Cheat Sheet provides five pieces of guidance that support such a goal.

1. Let the AI Loose on Your Application

One advantage of GenAI-driven testing is the automated generation of test suites. This typically creates hundreds or even thousands of tests with minimal human intervention. By letting the AI loose on your application, you significantly increase test coverage and uncover potential issues that might be missed with manual testing.

This approach saves time and also enhances the efficiency of your testing efforts. The AI will explore all the various pathways and scenarios within the application, providing a more thorough examination than traditional methods of creating test scripts.

2. Not Every Error is Equally Important

GenAI typically generates a vast number of tests and therefore often identifies vastly more defects than were found by traditional testing methods. Thus, it’s important to recognize that not every error is equally critical. Triage them to avoid inundating your development team with a barrage of low-priority issues. Be selective about which warrant immediate attention by identifying and prioritizing the most critical issues that truly impact the functionality and stability of the application.

3. Target Business Critical Functions

Maximize the benefits of GenAI by focusing its efforts on business-critical functions within your application. These are the areas where errors can have the most significant impact on user experience, data integrity, and overall system performance. By targeting these crucial functions, you ensure that the AI exhaustively tests pathways that are most vital to the success of your software.

4. Invest in Fine-Tuning the Training

GenAI’s effectiveness is further enhanced by investing time and resources in fine-tuning its training. While the AI excels at automatically generating tests, providing it with clear guidance on what not to test can be equally important. Work on refining the training data to exclude irrelevant scenarios or functionalities that do not significantly contribute to the overall quality of the application.

5. Tell the AI What Not to Test

As you guide the AI in its training, explicitly communicate what functionalities or pathways are less critical for testing. This strategic input helps the AI focus on areas of higher importance, saving time and resources. By striking a balance between instructing the AI on what to test and what not to test, you tailor its efforts to align with your specific testing goals.

Conclusion

A GenAI-powered testing platform like AIQ presents an exciting opportunity for software testing professionals to achieve a giant leap in performance. By leveraging the power of artificial intelligence, you can test more comprehensively, identify critical issues efficiently, and dramatically streamline your testing processes. Remember to guide the AI strategically, targeting business-critical functions and investing in fine-tuning its training to achieve optimal results. With GenAI, testing more and scripting less is not just a possibility, it’s a reality that will transform your testing operation.

Experience AIQ with a free demo.

Recent Blog Posts

Read Other Recent Articles

In the fast-evolving realm of technology, software testing is no longer a mere quality assurance process but a dynamic and multifaceted discipline that incorporates AI and autonomous systems. These technologies are increasingly revolutionizing the way we approach software quality. Let’s delve into the implications and future possibilities of AI and autonomous systems in testing and

In the fast-paced world of software development, ensuring the reliability and functionality of applications is paramount. Traditional methods of software testing rely on manually crafted test cases and data, which is time-consuming, expensive, and sometimes lacking in completeness. However, with the advent of Gen AI, there’s a paradigm shift in how test data is generated,

In the ever-evolving landscape of software development, ensuring the reliability and effectiveness of applications is paramount. As technology advances, so do the challenges in creating comprehensive test scenarios that mimic real-world conditions. One of the key components in achieving this is test data generation, and the integration of Gen AI is proving to be a

Empower Your Team. Unleash More Potential. See What AIQ Can Do For Your Business

footer cta image
footer cta image