Complete Competitive-Coding-1

[satish-paraddi]

No description provided.

[super30admin]

Interview Problem: Find Missing Number in a sorted array (Problem1.py)

Strengths:

1. Your solution uses binary search effectively, achieving O(log n) time complexity.
2. The logic of comparing ar[mid] - mid with the reference value is a clever approach.
3. The code is concise and readable.

Areas for Improvement:

1. Edge Case Handling: Your solution fails when the missing number is the last element in the sequence (e.g., [1, 2, 3, 4, 5, 6, 7] where 8 is missing). In this case, a remains -1 and ar[-1] + 1 gives incorrect results. You should handle this case by returning len(ar) + 1 or similar when a == -1.

2. Import Statement: You're using List[int] but haven't imported it. Add from typing import List at the top.

3. Variable Naming: The variable a is not descriptive. Consider renaming it to something like last_valid_index or breakpoint.

4. Documentation: Add a docstring explaining the approach and edge cases handled.

VERDICT: NEEDS_IMPROVEMENT

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Interview Problem: Design Min Heap (Problem2.py)

1. Correctness: Your solution correctly implements all the required operations (insert, removeMin, printHeap) and matches the reference solution's logic. The translation from C++ to Python is accurate.

2. Time/Space Complexity: Both complexities match the reference solution - O(log n) for insert/remove and O(n) for space.

3. Code Quality: The code is well-structured, readable, and follows Python best practices. Good use of comments documenting the complexities.

4. Minor Improvement: Consider adding input validation or error handling for edge cases (e.g., what happens when trying to insert into a full heap - currently it silently returns without notifying the user).

5. Pythonic Improvements: You could use Python's heapq module for comparison, but implementing it from scratch (as you did) is excellent for understanding the data structure.

VERDICT: PASS