Weighted edit distance
Compute a weighted edit distance between strings a and b where insert costs ci, delete costs cd, and substitute costs cs per single character (a matching character costs 0). Return the minimum total cost to transform a into b. Costs are positive integers; lengths up to ~1000.
Implement
weighted_edit_distance(a: str, b: str, ci: int, cd: int, cs: int) → intExamples
in
["abc","abd",1,1,1]out1What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 30 min
solution.py
InputExpectedGot
["abc","abd",1,1,1]1not run yetsample