Classic prefix sum problem but I fumbled the edge cases at first.
Start by clarifying the problem constraints (e.g., array size, element range) and then propose an efficient solution using prefix sums and a hash set to track seen sums. Explain that if a prefix sum repeats, the subarray between the two occurrences sums to zero. Analyze time and space complexity, and discuss edge cases like empty array or single element.
Pro tip: Mention that this problem is equivalent to finding two equal prefix sums, and that the hash set approach is optimal for unsorted arrays. Also, briefly note that for sorted arrays, a two-pointer approach could work, but it's not necessary here.
Ask about constraints: array size, whether the array can be empty, and if elements can be negative. Confirm that the subarray must be contiguous and non-empty.
Mention that a naive O(n^2) approach checks all subarrays, but it's inefficient for large inputs. This shows you understand the baseline.
Explain the prefix sum technique: iterate through the array, maintain a running sum, and use a hash set to store seen sums. If the current sum is 0 or already in the set, a zero-sum subarray exists.
State that time complexity is O(n) and space complexity is O(n) due to the hash set. This is optimal for unsorted arrays.
Discuss edge cases: empty array (return false), array with zeros (immediate true), and large arrays (efficient due to linear time).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.