We’ve all been there: tests fail for no obvious reason. The team says that something is random or that it cannot be reproduced and the related bugs get closed with no fix. Over time, the failures continue, sometimes mutating or multiplying. If not prioritized, these intermittent failures are often felt acutely by some team members, and they also adversely impact development cycle times. These bugs are fixable if you take the correct approach.
After an overview of why such errors occur, I will show how to visualize data sets that can be produced easily by automated tests. By properly visualizing detailed test results, it is possible to pinpoint the root causes of intermittent failures and therefore actually fix the underlying issues.