Competitve Coding-1

[mananrg]

No description provided.

[super30admin]

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

Strengths:

• Correct implementation of binary search for finding the missing element
• Clean, readable code with appropriate variable naming
• Good documentation with example inputs in comments
• Proper handling of edge cases (the while loop condition low <= high is correct)
• Optimal time and space complexity

Areas for Improvement:

• The function could benefit from input validation (e.g., checking if the array is empty or checking if the array is actually sorted)
• Consider adding more test cases to demonstrate the function works for different scenarios
• The function assumes the array starts from 1, which matches the problem statement but could be documented more explicitly

Minor Note:
The return statement return low + 1 works because low will point to the index where the first discrepancy occurs (where li[low] != low + 1). This is correct, though it might be slightly clearer to return li[low-1] + 1 when low > 0 to show the logical connection to the previous element.

VERDICT: PASS

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Interview Problem: Design Min Heap (Problem2.py)

Strengths:

• Clean, well-organized code that closely follows the reference solution's logic
• Correct implementation of all heap operations with proper edge case handling
• Good use of Python's tuple unpacking for swap operation
• Proper initialization with capacity-based array allocation

Areas for Improvement:

• Consider adding an explicit getMin() method for clarity, even though the functionality is available via heap[0]
• The printHeap() method could be enhanced to show the tree structure visually
• Could add input validation and error handling for edge cases
• Consider making the heap dynamic (resize when full) instead of fixed capacity

Overall, this is a solid implementation that demonstrates good understanding of heap data structures.

VERDICT: PASS