Edit distance
Return the Levenshtein edit distance between two strings a and b: the minimum number of single-character insertions, deletions, or substitutions needed to turn a into b. For example, turning "kitten" into "sitting" takes 3 edits. Either string may be empty. Strings can be up to a few thousand characters, so use O(len(a)*len(b)) time and try to keep memory to O(min(len(a), len(b))).
Implement
edit_distance(a: str, b: str) → intExamples
in
["kitten","sitting"]out3What 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 25 min
solution.py
InputExpectedGot
["kitten","sitting"]3not run yetsample