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```python def canPartitionKSubsets(nums, k): total = sum(nums) if total % k != 0: return False target = total // k memo = {} def backtrack(used, curr_sum, count): if count == k: return True if curr_sum > target: return False if (used, curr_sum, count) in memo: return memo[(used, curr_sum, count)] for i in range(len(nums)): if not (used & (1 << i)): if curr_sum + nums[i] <= target: if backtrack(used | (1 << i), curr_sum + nums[i], count): memo[(used, curr_sum, count)] = True return True if curr_sum == target: if backtrack(used, 0, count + 1): memo[(used, curr_sum, count)] = True return True memo[(used, curr_sum, count)] = False return False return backtrack(0, 0, 0) ``` Which line contains the subtle bug?

medium🐞 Bug Identification Q7 of Q15
Subsets & Combinations - Partition to K Equal Sum Subsets
Analyze the following Python code snippet for partitioning an array into k equal sum subsets using backtracking with bitmask memoization. Identify the logical error that can cause incorrect results. ```python def canPartitionKSubsets(nums, k): total = sum(nums) if total % k != 0: return False target = total // k memo = {} def backtrack(used, curr_sum, count): if count == k: return True if curr_sum > target: return False if (used, curr_sum, count) in memo: return memo[(used, curr_sum, count)] for i in range(len(nums)): if not (used & (1 << i)): if curr_sum + nums[i] <= target: if backtrack(used | (1 << i), curr_sum + nums[i], count): memo[(used, curr_sum, count)] = True return True if curr_sum == target: if backtrack(used, 0, count + 1): memo[(used, curr_sum, count)] = True return True memo[(used, curr_sum, count)] = False return False return backtrack(0, 0, 0) ``` Which line contains the subtle bug?
AThe check 'if curr_sum > target' should be after the for-loop, not before.
BThe memoization key includes 'curr_sum' which can cause redundant states.
CThe base case 'if count == k' should check if all elements are used instead.
DThe recursive call inside the for-loop uses 'count' instead of 'count + 1' when curr_sum reaches target.
Step-by-Step Solution
Solution:
  1. Step 1: Understand the recursion parameters

    curr_sum tracks sum of current subset; count tracks how many subsets formed.
  2. Step 2: Identify when to increment count

    When curr_sum == target, we should start forming next subset (count + 1).
  3. Step 3: Locate the bug

    Inside the for-loop, recursive call uses 'count' even when curr_sum reaches target, missing subset increment.
  4. Final Answer:

    Option D -> Option D
  5. Quick Check:

    Subset count must increment exactly when subset sum reaches target [OK]
Quick Trick: Increment subset count only when current sum equals target [OK]
Common Mistakes:
MISTAKES
  • Not incrementing count when subset sum completes
  • Incorrect memoization keys causing inefficiency
  • Misplaced base case checks
Trap Explanation:
PITFALL
  • Using 'count' instead of 'count + 1' causes subsets to not increment properly, leading to wrong results.
Interviewer Note:
CONTEXT
  • Tests ability to spot subtle logical errors in recursive backtracking code.
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