Find Largest Sum Contiguous Subarray
Reported by candidates from Cisco's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Cisco asked this in August 2024, and it's a classic that trips candidates who overthink it. You're looking for the contiguous subarray with the largest sum across an array of integers, possibly negative. It's not about finding the longest subarray or the one with the most elements. It's pure sum. Kadane's algorithm solves it in one pass. If you blank during the live OA, StealthCoder will feed you the pattern and structure so you don't crater.
Pattern and pitfall
This is Kadane's algorithm territory. The trick is tracking two numbers: the max sum ending at the current index, and the global max seen so far. At each element, you decide: extend the previous subarray or start fresh from here. The common pitfall is trying to track indices or overthinking prefix sums. The greedy insight is that if your running sum goes negative, dump it and start over from the next element. It's O(n) time, O(1) space. During the OA, if the wording feels ambiguous about negative numbers or empty subarrays, StealthCoder will clarify the edge cases so you don't code the wrong problem.
StealthCoder is the hedge for the one pattern you didn't drill. It runs invisibly during the screen share.
You can drill Find Largest Sum Contiguous Subarray cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. If you're reading this with an OA window open, you're who this was built for.
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Find Largest Sum Contiguous Subarray FAQ
Does Kadane's algorithm handle all-negative arrays?+
Yes. It returns the least negative number, not zero or empty. The maximum subarray is still a subarray, even if all values are negative. So for [-3, -1, -4], the answer is -1. Most candidates try to return 0, which is wrong.
Do I need to track the start and end indices?+
Not for this problem if the question only asks for the sum. But Cisco might ask for the subarray itself or its indices. Extend Kadane by tracking start, temp_start, and end pointers. Update end and indices only when you find a new global max.
Can the subarray be empty?+
No. A subarray must contain at least one element. This is a key constraint. If the problem says otherwise, re-read it. Cisco will follow the standard definition.
Is there a prefix sum approach?+
Yes, but it's slower. You can compute all prefix sums and track the min prefix, then find max(prefix[i] - min_prefix). It's O(n) time but O(n) space. Kadane is better. Use it.
What if the array is very large, like 10^6 elements?+
Kadane still runs comfortably. O(n) time and O(1) space mean you process 10^6 elements in milliseconds. No optimization tricks needed. Focus on correct logic, not premature optimization.