It’s essential to approach this collaboratively. I’d start by sharing specific examples of the test results, highlighting the potential impact on user experience or system performance. Open dialogue is key—inviting developers to discuss the findings together can lead to a better understanding of the issues at hand. Ultimately, we all want the same outcome: a high-quality product.

Run the same test on their machine in front of them. This way I collaborate, present data visually and provide context to exactly what is going wrong and where. If they have any further questions, I will help them with more information and clear all the doubts required to categorize the test results as Pass or Fail.

I usually follow these approaches to effectively convey issues and test reports to developers while maintaining a good relationship with them. First, I record the testing process to accurately depict the issue and provide clear, reproducible steps. If they still aren’t convinced, I schedule a call with the developer to explain and demonstrate the specific issues and where the testing team has encountered blockers.

To convince developers of disparities in test results, I clearly present the data with evidence, showing specific issues and how to reproduce them. I emphasize the impact on user experience and invite their feedback to foster collaboration, building trust and understanding around the importance of addressing these findings.

Disparities in what? This is yet another garbage word-salad AI article prompt lacking sufficient clarity to support a cohesive answer.