Grokking the Coding Interview: Patterns for Coding Questions
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Solution: Pangram

Problem Statement

Given a string sentence containing English letters (lower- or upper-case), return true if sentence is a Pangram, or false otherwise.

A Pangram is a sentence where every letter of the English alphabet appears at least once.

Note: The given sentence might contain other characters like digits or spaces, your solution should handle these too.

Example 1:

Input: sentence = "TheQuickBrownFoxJumpsOverTheLazyDog"
Output: true
Explanation: The sentence contains at least one occurrence of every letter of the English alphabet either in lower or upper case.

Example 2:

Input: sentence = "This is not a pangram"
Output: false
Explanation: The sentence doesn't contain at least one occurrence of every letter of the English alphabet.


We can use a HashSet to check if the given sentence is a pangram or not. The HashSet will be used to store all the unique characters in the sentence. The algorithm works as follows:

  1. Converts the sentence to lowercase.
  2. Iterate over each character of the sentence using a loop.
  3. Add each character to the HashSet.
  4. After looping through all characters, compare the size of the HashSet with 26 (total number of alphabets). If the size of the HashSet is equal to 26, it means the sentence contains all the alphabets and is a pangram, so the function will return true. Otherwise, it will return false.


Here is the code for this algorithm:


. . .
You must run your code first

Time Complexity

  1. Iterating Over Characters: The main operation in the code is iterating over each character in the input string. If the length of the input string is n, this iteration occurs n times.

  2. Set Operations: For each character, the code performs a constant-time operation—adding the character to a HashSet if it's a letter. The time complexity for adding an element to a HashSet is typically O(1).

  3. Overall Time Complexity: Considering the iteration over n characters and constant-time set operations, the total time complexity is O(n), where n is the length of the sentence.

Space Complexity

  1. HashSet Storage: The HashSet seen is used to store the distinct characters encountered in the sentence. In the worst-case scenario, it will store all 26 letters of the alphabet.

  2. Constant Size Set: Regardless of the input sentence length, the HashSet can only grow up to a size of 26. This is because it only stores distinct English alphabet letters.

  3. Overall Space Complexity: Given the HashSet's maximum size is constant (at most 26 characters), the space complexity is O(1), meaning it is constant.


  • Time Complexity: O(n), where n is the length of the input string.
  • Space Complexity: O(1) (constant space, independent of input string length).
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