DSA Problem-Solving Checklist (To Train Patterns)

1. Understand & Restate the Problem

• What is the input?
• What is the output?
• What exactly is being asked?
• Restate in your own simple words (this makes sure you really understand).

2. Identify Constraints

• Input size? (Helps decide if brute force is possible or not)
• Value limits? (Helps decide data types, possible overflows, modulo, etc.)
• Is the input sorted, unique, graph, string, etc.?

3. Classify the Problem (Pattern Recognition)

• Which category does it belong to?
• Why? (state one line: “I see overlapping subproblems → DP”).

4. Brute Force Approach

• Think: “If constraints were very small, how would I solve it?”
• Outline steps.
• Analyze time & space.

5. Optimized Approach

• Think: “How do I reduce repeated work?”
• Patterns:
• Write the high-level idea first (not code).

6. Base Cases / Edge Cases

• What’s the smallest valid input?
• Any tricky cases (empty array, negative numbers, single element, max constraints)?
• Handle them explicitly.

7. Step-by-Step Logic (in Plain English)

• Before coding, explain your algorithm like teaching a 10-year-old.
• Example: “Loop through array, keep a running sum, if I’ve seen (sum-k) before, then subarray exists.”

8. Code Skeleton

• Write pseudocode first.
• Then convert into real code.
• Keep functions small & clear.

9. Dry Run Example

• Use small input and simulate manually.
• Make a table: variables changing at each step, final result.
• Do at least one normal case + one edge case.

10. Complexity Analysis

• Time complexity (Big-O).
• Space complexity (extra structures, recursion depth).
• Justify why.

11. Real-World Analogy (Optional but Powerful)

• Relate to something intuitive.

12. Interview Tips

• Always say your thought process out loud.
• Start with brute force → then optimize.
• Mention trade-offs (time vs. space).
• Don’t jump to code immediately.