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This approach uses two pointers to simultaneously traverse both strings. The goal is to see if `str2` can be formed as a subsequence of `str1` with at most one cyclic increment operation. During the traversal, if `str1[i]` can be incremented to match `str2[j]` by a cyclic shift, move both pointers forward. If `str1[i]` cannot be shifted to match `str2[j]`, and only one operation is allowed, then return false. Otherwise, continue checking until either `str2` is fully traversed (return true) or `str1` is exhausted (return false).
Time Complexity: O(n + m), where n is the length of `str1` and m is the length of `str2` since we process each character once.
Space Complexity: O(1), since no additional space proportional to input size is used.
1def can_form_subsequence(str1: str, str2: str) -> bool:
2 i = j = 0
3 n, m = len(str1), This Python solution uses loop iteration and the `ord` function to perform cyclic checks on character indices. The code ever so slightly resembles a `two pointer technique`, ensuring every approved character contributes to forming a proper subsequence of `str2` from `str1`.
This method determines the feasibility of forming `str2` as a subsequence by transforming `str1` using character frequency transitions, considering cyclic alphabet rules. Using a frequency map for `str1`, iterate through `str2`, checking if corresponding increments can map `str1` characters to those in `str2`. For each character needed in `str2`, see if it's obtainable via allowable operations on `str1` characters, optimizing through potential full rotations using the alphabet cycle property.
Time Complexity: O(n + m + 26) to cover all characters and frequency evaluations.
Space Complexity: O(1), preserving essential space outside of constant size arrays.
Python's solution conducts character transformation checks by maintaining a frequency register for `str1`, testing potential transformations in seeking sub-sequential emergence within `str2`. Prompt checking ceases unsuccessful allocation.