Solution

Method 1 – Block Preprocessing and Greedy Simulation per Query

Intuition

For each query substring, we want to maximize the number of '1's after at most one trade (remove a block of '1's surrounded by '0's, then flip a block of '0's surrounded by '1's). We preprocess the substring for all such blocks and simulate all possible trades for each query.

Approach

For each query [l, r], extract s[l..r] and augment as t = '1' + s[l..r] + '1'.
Find all blocks of '1's surrounded by '0's and all blocks of '0's surrounded by '1's in t.
For each possible pair (remove a '1' block, flip a '0' block), simulate the trade:
- Remove the '1' block (set to '0'), then flip the '0' block (set to '1').
- Count the number of '1's in the resulting string (excluding the augmented ends).
- Track the maximum.
If no valid trade, return the count of '1's in the substring.
Repeat for all queries and return the results.

Code

[{"language":"Python","code":"class Solution:\n    def maximizeActiveSections(self, s: str, queries: list[list[int]]) -> list[int]:\n        res = []\n        for l, r in queries:\n            sub = s[l:r+1]\n            t = '1' + sub + '1'\n            n = len(t)\n            ones, zeros = [

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