Jonathan Lipps on Mobile Testing Challenges & the Role of AI at Selenium & Appium

About The Video

Watch this insightful discussion with 𝐉𝐨𝐧𝐚𝐭𝐡𝐚𝐧 𝐋𝐢𝐩𝐩𝐬, as he dives into the evolving world of mobile testing, its challenges, and how AI is transforming the mobile landscape.

Jonathan shares his experiences with Appium, the slow pace of change in mobile testing tools, and the impact of AI on the mobile app space. He also discusses the potential of Model Context Protocol (MCP) and its role in simplifying the testing process.

He also provides his perspective on AI's limitations and the importance of maintaining human creativity in areas like music and personal expression. Tune in for a balanced look at the future of mobile testing, AI, and the evolving developer experience.

Key Takeaways

Evolution of Mobile Testing:

Mobile testing has evolved from a niche activity to an essential part of app development. It's now a requirement to automate tests for mobile apps, and mobile testing is a core part of the development process.

Lack of New Tools in Mobile Testing:

Despite the growth in mobile testing, there has been relatively little innovation in the tools available for it, especially when compared to the rapid development of web testing tools. Appium remains a cornerstone in mobile testing, but there are fewer new tools in the mobile space compared to web testing frameworks like Selenium, Playwright, and Cypress.

Restrictions in Mobile Platforms:

The major challenge in mobile testing is the limited access to tools, especially due to the restrictions from mobile operating system providers like Apple. This limits the ability to create fully open-source tools and forces reliance on the platforms’ proprietary tools (e.g., Xcode for iOS).

Challenges with Apple's Tools:

Jonathan highlights the difficulty in setting up mobile test environments, particularly on iOS, which takes a lot of time and energy. He expresses a desire for more accessible and reliable tools from Apple to improve the experience of testing on iOS devices.

AI in Mobile Testing:

While AI is being incorporated into various industries, Jonathan expresses skepticism about its transformative impact on mobile testing. Although AI tools like test suggestion engines are useful, they are not revolutionary or groundbreaking in the same way AI in web development has been.

AI's Role in Enhancing Developer Experience:

Jonathan appreciates tools like MCT (Mobile Component Testing) that help developers focus on the relevant actions in mobile app testing, emphasizing that AI should not be seen as a "magic assistant" but as a tool that provides structure and direction in the testing process.

Limitations of Large Language Models (LLMs):

He discusses the limitations of LLMs like GPT, which may generate inaccurate information (referred to as "hallucination"). In contrast, tools connected to trusted APIs or frameworks (like Appium) can be more reliable as they perform actions that are verifiable and based on real-world interactions.

AI in General and Philosophical Considerations:

Jonathan touches on the broader philosophical implications of AI, cautioning against using AI for tasks that should remain human, such as emotional support or creative endeavors. He advocates for a balanced approach where AI supports tasks like testing but doesn’t replace the human touch in more personal or creative roles.

AI's Role in the Future of Work:

Looking to the future, Jonathan stresses the importance of understanding both the capabilities and limitations of AI in the workplace. He encourages individuals to use AI for practical tasks but to retain the human element in areas like creative expression and problem-solving.