The longest common prefix of two words is the longest word that both words start with. For example,
the longest common prefix of the words identity
and idealistic
is the word ide
.
A database contains words.
The algorithm to search for a query word in the database is primitive. It compares the word one by one with each word in the database. Two words are compared letter by letter until a letter in which they differ is found or until the end of one of the words is reached (it is then established either that the words are equal or that one is longer than the other). When the algorithm finds the word in the database, it terminates.
Analysing the algorithm shows that the number of steps needed to find a word is equal to the number of words is compared to, plus the sum of the lengths of the longest common prefixes of and each of the words it was compared to.
Write a program that calculates the number of steps the algorithm uses to find each of the query words.
Input Specification
The first line contains an integer , the number of words in the database.
Each of the following lines contains a single word from the database. The words are given in the order the algorithm compares them to a query word. All words in the database will be distinct.
The following line contains an integer , the number of words searched for.
Each of the following lines contains a single query word.
All words in the input will be strings of less than lowercase letters of the English alphabet.
Output Specification
Output one integer per line for each query word, the number of steps the algorithm uses when searching for the word.
Sample Input 1
5
hobotnica
robot
hobi
hobit
robi
4
robi
hobi
hobit
rakija
Sample Output 1
12
10
16
7
Sample Input 2
8
majmunica
majmun
majka
malina
malinska
malo
maleni
malesnica
3
krampus
malnar
majmun
Sample Output 2
8
29
14
In the second example, the number of steps to search for the word krampus
is because the
algorithm only needs to compare its first letter to each word in the database.
When searching for the word malnar
, we need three steps for each of the first three words, and four
steps for each of the remaining five words, for a total of steps.
To find the word majmun
we use a total of steps. For the first word in the database, we have six
successful comparisons and one step in which we determine that the word majmunica
is longer than
the query word. For the second word, we also have six successful comparisons and a final step in which
it is established that the words are equal. After finding the word, the algorithm terminates with great
joy.
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