Test: Tries - 1 - Software Development MCQ

Tries are tree-like data structures commonly used to store and retrieve strings. Each node represents a character, and the edges represent the next characters in the strings.

In a Trie, each node typically contains multiple characters and a pointer to the child node. The child node represents the next character in the string.

Although it is possible to retrieve strings from a Trie in lexicographic order, it is not a typical operation supported by Tries. The main operations supported by Tries are insertion, search, and prefix matching.

The time complexity for searching a string in a Trie is proportional to the length of the searched string. It requires traversing the Trie from the root to the leaf node corresponding to the last character of the string.

Tries can be used to efficiently check whether two strings are anagrams. By inserting one string into a Trie and then searching for the other string, we can determine if they have the same characters in the same quantities.

The output of the code will be:
1
0
1
The code creates a Trie and inserts the strings "apple", "banana", and "cat". It then searches for the strings "apple", "dog", and "cat" using the 'search' function. The function returns 1 if the string is found in the Trie and 0 otherwise.

The output of the code will be:
1
1
0
The code creates a Trie and inserts the strings "apple", "banana", and "cat". It then checks if the Trie contains strings starting with the characters "a", "b", and "d" using the startsWith function. The function returns 1 if there are strings 'starting with' the given prefix and 0 otherwise.

The output of the code will be:
0
1
The code creates a Trie and inserts the strings "apple", "banana", and "cat". It then removes the string "apple" from the Trie using the 'remove' function. After that, it 'searches' for the strings "apple" and "banana" using the search function. The function returns 1 if the string is found in the Trie and 0 otherwise.

The output of the code will be:
The code creates a Trie and inserts the strings "apple", "banana", and "cat". It then counts the number of strings with the prefixes "a", "b", and "ca" using the 'countPrefixes' function. The function returns the count of strings with the given prefix.

The output of the code will be:
apple
""
cat
The code creates a Trie and inserts the strings "apple", "banana", and "cat". It then finds the longest prefix of the given strings using the 'longestPrefix' function. The function returns the longest prefix that exists in the Trie for each given string.

To build an auto-complete feature using a Trie, you need to insert all the strings into the Trie. Then, when the user enters a partial string, you can use the search function to find matching prefixes and suggest possible completions.

To implement the 'search' function that checks if a word exists in the Trie, you can use recursion to traverse the Trie and compare each character of the word with the corresponding nodes in the Trie.

To count the number of strings with a given prefix in a Trie, you can use recursion to traverse the Trie until reaching the last character of the prefix. Then, you can count the number of strings below that point.

To find the longest duplicate substring in a list of words using a Trie, you can insert all the words into the Trie and then use a depth-first search to find the longest duplicate substring.

To implement the 'remove' function that removes a word from the Trie, you can use recursion to traverse the Trie and locate the nodes corresponding to the characters of the word. Once you reach the last character, you can remove the nodes in reverse order.