Problem Solving In Data Structures & Algorithms... May 2026

Dealing with "Top K" elements or frequently updated minimums/maximums. 3. The "Rubber Duck" Debugging Technique

A solution is only as good as its handling of the "weird stuff." Always test for: (null, empty strings, 0). Single elements (an array of size 1). Large inputs (integer overflows). Duplicates (especially in sorting or searching). The Golden Rule Problem Solving in Data Structures & Algorithms...

Finding subarrays or substrings (e.g., "Longest substring without repeating characters"). Dealing with "Top K" elements or frequently updated

Look for redundant work. Are you recalculating the same value? (Use Dynamic Programming ). Are you searching linearly? (Use Binary Search or a Hash Map ). 2. The Mental Toolkit (Pattern Recognition) Single elements (an array of size 1)

Always identify the "Brute Force" solution first. Even if it’s inefficient, it guarantees a baseline for correctness and helps you see where the bottlenecks are.

If you get stuck, explain the logic out loud to an inanimate object (or yourself). Translating abstract thoughts into spoken words often exposes the "logic gap" that your brain was subconsciously skipping over. 4. Implementation & Edge Cases

Get it working first, then make it fast, then make it clean.