Quick revision

| Auxiliary Space | extra space or temporary space used by an algorithm, excluding the space for the output

It does not use any data structures that grow with the input size, so the space complexity is O(1), which is constant. | | --- | --- | | Amortised | computes the average cost per operation over a (worst-case) sequence of operations by spreading occasional expensive steps across many cheap ones

• Although a single insert into a dynamic array may sometimes take O(n) when resizing, its amortised cost over n inserts is O(1). • Union-Find’s find uses path compression, giving O(α(N)) amortised per operation, which for practical N is constant. | | | | | | |

Technical coding test tips

✅ Shortened "Strong Hire" Checklist (for quick reference)

• [ ] 1. Restate Problem Clearly
• [ ] 2. Clarify Constraints Explicitly
• [ ] 3. Outline & Confirm Test Cases
• [ ] 4. Compare Solutions (Naïve vs Optimal)
• [ ] 5. Discuss Complexity (Time & Space)
• [ ] 6. Confirm Approach with Interviewer
• [ ] 7. Write Modular & Commented Code
• [ ] 8. Actively Test Edge Cases
• [ ] 9. Propose Optimisations & Discuss Trade-offs
• [ ] 10. Confidently Summarise & Close

🎯 Mindset of a Strong Hire:

• Clear & confident communication.
• Proactive problem clarification.
• Explicitly compares approaches.
• Thoroughly tests with examples & edge cases.
• Writes readable, modular, and maintainable code.
• Actively seeks interviewer’s feedback.

Step 1: Restate and Confirm Understanding

• Clearly rephrase the problem statement back to the interviewer.

  Example: "Just to confirm, given an unsorted array of integers, I need to return the indices of two numbers that sum up to a target value?"

Step 2: Clarify Inputs, Outputs, and Constraints

• Ask targeted clarifying questions:
  • "Are there negative numbers? Duplicate values?"
  • "What’s the input size—should I optimise for speed, memory, or balance both?"
  • "Can the input array be modified in-place?"

Step 3: Outline Test Cases (Including Edge Cases)

• Proactively suggest at least 3 cases:
  • Simple/Base: [1, 2, 3, 4], target = 5 → [0, 3]
  • Edge: Empty input ([]), Single-element array ([1])
  • Complex: Large values, negative numbers, duplicates ([-1, 0, 2, -2, 3] target = 1)