The answer is 2.
How do I know know this? Simple, I applied the generalized edit distance algorithm. This algorithm measures the similarity between two words or phrases (i.e., strings).
Measuring the distance between two words is useful for search engines, handwriting recognition, and speller checkers.
To understand how the generalized edit distance works, read on.
Reina Käärik succinctly explains how the generalized edit distance works.
Edit distance, also known as Levenshtein distance, is used to measure the minimal number of edit steps that has to be
made to transform one string to another. Allowed transformations (or edit steps) are:
For instance, the edit distance between health and heart is 2.
- Step 0: health
- Step 1 (Replace l with r): hearth
- Step 2 (Delete h): heart
For another example, the edit distance between heart and horror is 4.
- Step 0: heart
- Step 1 (Replace e with r): hoart
- Step 2 (Replace a with r): horrt
- Step 3 (Replace t with o): horro
- Step 4 (Add r): horror