When debugging algorithms under time pressure, I prioritize symptoms over specifics, focusing on observable behavior and error messages to narrow down the issue. If consistent reproduction is difficult, I use hypothesis-driven testing, modifying parts of the code or simulating edge cases to validate each hypothesis quickly. Additionally, I collaborate with teammates for fresh insights, as they may have specific knowledge about the deployment environment. This combination of targeted testing and teamwork helps me efficiently identify and resolve bugs under tight deadlines.

Few things I have found useful are- - Use the right environment, data and user/system role - Have clarity on possible scenarios - Execute the happy path or the closer (to the scenario) path that works - Leverage logs, breakpoints, display messages - Identify the code block where it breaks - check for reasons and correct your code

1. Break the Algorithm into Sections: Divide the algorithm into smaller components to isolate the part causing the issue. 2. Test with Edge Cases: Use extreme or minimal inputs to quickly expose the bug’s behavior. 3. Binary Search for Bugs: Gradually narrow down the problematic code by testing smaller segments of the algorithm. 4. Analyze Inputs and Outputs: Check if the inputs are processed as expected at each step to identify where things go wrong. 5. Check Assumptions: Ensure no hidden assumptions or unhandled cases are overlooked in the code logic.

To quickly debug an algorithm under pressure, I'll consider the following strategies: Check Recent Changes: Begin by reviewing the most recent code modifications, as new changes often introduce bugs. Simplify Test Cases: I'll Create minimal input examples that consistently reproduce the bug. Simpler cases make it easier to identify the problem. I'll isolate sections of code or use a binary search approach to narrow down where the bug occurs. Utilize Debuggers and Logging: I'll use a debugger to observe variable states and program flow. Implement logging to capture runtime information without stopping execution. Review Algorithm Logic: Re-examine the core logic to confirm it aligns with the required design and principles.