Elevating QA with AI: My Journey in Automating Manual Testing
In the fast-evolving landscape of AI, automating end-to-end (e2e) manual testing is reshaping quality assurance. I recently explored this potential in testing the RudderStack iOS SDK, which tracks customer event data. Here’s a snapshot of my experience:
Key Insights:
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Challenges Faced:
- Manual testing involved lengthy and error-prone steps.
- Required meticulous planning and interaction verification.
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Innovative Solutions:
- Leveraged LLMs to streamline test planning and execution.
- Employed mobile-mcp for user interaction simulation and log verification.
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Results Achieved:
- Successfully identified regression issues.
- Improved consistency compared to traditional manual methods.
Key Takeaway: While the initial setup demands extensive detail and effort, the value lies in achieving reliable regression testing over mere speed.
Have you experimented with AI in QA? Share your experiences and insights! Let’s build a community of learning together.
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