Coverage illusion is the false sense of confidence that comes from having high test coverage numbers without actually testing what matters. It happens when metrics suggest that a system is well tested, but important behaviours, risks, or failure scenarios remain unexamined.
This illusion often appears when tests focus on executing lines of code rather than validating outcomes. For example, a test may pass through a piece of logic without checking whether the result is correct, or it may avoid meaningful edge cases while still increasing coverage percentages.
Coverage illusion is risky because it shifts attention from understanding behaviour to chasing numbers. Teams may believe the system is safe to release because coverage looks good, even though critical paths, integrations, or assumptions have not been tested properly.
Avoiding coverage illusion means treating coverage as a signal, not a goal. Good testing looks beyond what was executed and asks what was actually verified, what could go wrong, and what evidence exists that the system behaves as intended under real conditions.
This illusion often appears when tests focus on executing lines of code rather than validating outcomes. For example, a test may pass through a piece of logic without checking whether the result is correct, or it may avoid meaningful edge cases while still increasing coverage percentages.
Coverage illusion is risky because it shifts attention from understanding behaviour to chasing numbers. Teams may believe the system is safe to release because coverage looks good, even though critical paths, integrations, or assumptions have not been tested properly.
Avoiding coverage illusion means treating coverage as a signal, not a goal. Good testing looks beyond what was executed and asks what was actually verified, what could go wrong, and what evidence exists that the system behaves as intended under real conditions.
