The base case is fine, just a sliding window.
Start by clarifying the problem and edge cases, then present a linear-time sliding window solution for the base case. For the follow-up, extend the approach by tracking the length of increasing runs and considering replacements at boundaries, aiming for an O(n) solution.
Pro tip: Explicitly state the time and space complexity of your solution and discuss potential optimizations or alternative approaches, showing you think beyond the immediate problem.
Ask clarifying questions about input constraints, definition of 'strictly increasing', and whether the replacement can be any integer. Confirm that the subarray must be contiguous.
Explain a sliding window or two-pointer approach to find the longest strictly increasing contiguous subarray in O(n) time. Track the start of the current increasing run and update the maximum length.
For the follow-up, consider how replacing one element can merge two increasing runs. Identify that the replacement is most beneficial at the boundary between two runs, where the element breaks the increasing order.
Propose an O(n) algorithm: precompute lengths of increasing runs ending at each index and starting at each index. Then, for each potential replacement point, calculate the maximum length by combining runs if the replacement can bridge them.
Walk through examples to validate the approach, including edge cases like all increasing, all decreasing, or single element. Summarize the solution and its complexity.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.