What are the common pitfalls in visual testing?

The common pitfalls in visual testing often stem from an over-reliance on automated tools, neglecting the importance of manual reviews, and failing to properly define baselines. Automated tools can be incredibly helpful in identifying visual discrepancies, but they are not foolproof. Relying solely on these tools can lead to missed context-specific issues that only a human reviewer might catch.

Additionally, without well-defined baselines, it becomes challenging to determine what constitutes an acceptable visual state. Baselines serve as a reference point for comparison; without them, tests may yield misleading or inconclusive results. Manual reviews are crucial for assessing visual integrity and ensuring that the end product meets design specifications, as human judgment can account for nuances that automated tools cannot.

In contrast, the other choices highlight aspects that are less central to the challenges faced in visual testing. For instance, while using too many performance metrics may muddy the decision-making process, it doesn't directly address visual testing pitfalls. Focusing solely on user feedback and exclusively testing on mobile platforms represent narrower points of concern that do not encompass the broader challenges present in visual consistency and accuracy across platforms.