Pretty standard stuff, single pass tracking a running count and a max.
Start by clarifying the problem and edge cases, then propose a single-pass linear scan that tracks the current run of 1s and updates the maximum. Discuss time and space complexity, and offer to code the solution with clear variable names and tests.
Pro tip: Mention that this is a classic sliding window/counting problem and that the same pattern extends to finding the longest subarray with at most K zeros or ones, showing you understand the underlying technique.
Confirm the input is a binary array (only 0s and 1s) and that we need the length of the longest contiguous subarray of 1s. Ask about edge cases like empty array or all 1s.
Propose a single-pass scan: maintain a current count of consecutive 1s and a maximum count. Reset current count to 0 when encountering a 0, and update maximum when current exceeds it.
State that the algorithm runs in O(n) time and O(1) space, which is optimal since every element must be examined at least once.
Write clean code with meaningful variable names (e.g., maxStreak, currentStreak). Handle edge cases such as empty array by returning 0.
Walk through a few test cases: [1,1,0,1,1,1] returns 3, [0,0,0] returns 0, [1,1,1,1] returns 4. Mention that the solution is robust.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
First, clarify that the circular array allows a run to wrap around, so the maximum run is either entirely within the array or spans the boundary. Compute the maximum run without wrap using a linear scan, and also compute the total number of 1s; if the array is all 1s, the answer is n, otherwise the maximum wrap-around run is the sum of the leading 1s and trailing 1s. Return the maximum of these two values.
Pro tip: Mention edge cases upfront, like all 1s or no 1s, and note that the wrap-around run can only be formed by the suffix and prefix, not by concatenating arbitrary segments. This shows attention to detail and avoids common pitfalls.
Confirm that the array is circular and a run can wrap around. Discuss edge cases: all 1s, no 1s, and arrays with only one 1.
Perform a linear scan to find the longest consecutive sequence of 1s in the non-circular array. Keep track of the current run and the maximum run.
Count the total number of 1s. If it equals the array length, the answer is n. Otherwise, proceed to compute the wrap-around run.
Find the length of the prefix of 1s and the suffix of 1s. The maximum wrap-around run is the sum of these two lengths, but only if there is at least one 0 in the array (otherwise it would be the whole array).
Return the maximum of the non-wrap run and the wrap-around run. Discuss time and space complexity: O(n) time, O(1) space.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.