Many candidates write code that's 90% correct but fail interviews because they can't debug the final 10%. A systematic approach is crucial: first reproduce the bug consistently with the exact failing input. Then isolate the problem using print statements or tracing to check intermediate values. Form a hypothesis about the root cause, like an off-by-one error or incorrect initialization.

Common mistake categories include off-by-one errors in loop bounds, initialization mistakes, and poor edge case handling. For example, initializing a max value as 0 fails for negative numbers. State management errors, like forgetting to update a set or updating in the wrong order, are frequent in sliding window or two-pointer problems. Recognizing these patterns accelerates diagnosis.

Practical techniques include print statement debugging, rubber duck debugging, and reducing test cases to the minimal failing input. In interviews, communicate your process: trace through the code, identify the divergence, and make a targeted fix. Tools like IDE debuggers help, but print statements are often faster for quick checks. The goal is to build resilience and methodical thinking under pressure.