Done Competitive-Coding-1

[samikshm]

No description provided.

[super30admin]

Problem 1 (Missing Number):

• The binary search approach is correct and well-implemented for finding the missing number in a sorted array where nums[i] == i + 1 before the missing element.
• The code handles the edge case where the missing number could be at the end (returns low + 1 correctly).
• However, there's a potential bug: if the array is empty, high = nums.length - 1 would be -1, and the while loop wouldn't execute, returning low + 1 = 1, which is incorrect for an empty array.
• The algorithm correctly identifies the first mismatching position and returns the missing number.

Problem 2 (Min Heap):

• The min heap implementation is well-structured with clear separation of concerns (push, pop, peek, size, heapify, swap).
• The bubble-up logic in push and heapify-down logic in pop are correctly implemented.
• Edge cases are handled: pop on empty heap returns gracefully, peek on empty heap returns -1.
• The heapify method correctly finds the smallest among parent, left child, and right child.
• The implementation follows proper OOP principles with private helper methods.

Areas for Improvement:

1. Problem 1: Add a check for empty array at the beginning.
2. Problem 2: Consider adding a method to check if the heap is empty rather than relying on size() == 0 checks.
3. Both solutions could benefit from more descriptive variable names (e.g., mid could be midIndex).
4. Problem 2: The peek method returning -1 for empty heap is a design choice - consider throwing an exception or documenting this behavior.