What is the time complexity of Number of Strings That Appear as Substrings in Word?

The optimal solution for Number of Strings That Appear as Substrings in Word runs in O(n + m) time and uses O(n) space. This complexity is due to the time taken to create a set of unique patterns (O(n)) and the substring search in the word (O(m)).

What is the brute force solution for Number of Strings That Appear as Substrings in Word?

The brute force approach for Number of Strings That Appear as Substrings in Word is Brute Force, with O(n * m) time complexity and O(1) space complexity. The brute-force approach checks each pattern against the word one by one. This is straightforward but can be inefficient as it involves repeated substring searches. The optimal Optimal Solution approach improves this to O(n + m).

What algorithm or data structure is used to solve Number of Strings That Appear as Substrings in Word?

Number of Strings That Appear as Substrings in Word uses the following concepts: Array, String. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Number of Strings That Appear as Substrings in Word?

Always clarify if duplicates in patterns should be counted multiple times. Discuss your thought process and consider edge cases, like empty patterns or words. Optimize your solution after presenting the brute-force approach to show your problem-solving skills.

What are common mistakes when solving Number of Strings That Appear as Substrings in Word?

Not considering duplicates in patterns, leading to overcounting. Failing to use efficient string search methods, resulting in unnecessary complexity.

#1967

Number of Strings That Appear as Substrings in Word

Easy

ArrayStringHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n * m)	O(n + m)
Space	O(1)	O(n)

💡

Intuition

Time O(n + m)Space O(n)

Using a set to store patterns allows for efficient membership testing. This reduces the need for repeated substring searches and improves performance.

⚙️

Algorithm

5 steps

1Step 1: Convert the patterns list into a set to eliminate duplicates.
2Step 2: Initialize a count variable to 0.
3Step 3: For each pattern in the set, check if it exists in the word using the built-in substring function.
4Step 4: If it exists, increment the count.
5Step 5: Return the count after checking all patterns.

solution.py7 lines

1def count_patterns(patterns, word):
2    unique_patterns = set(patterns)
3    count = 0
4    for pattern in unique_patterns:
5        if pattern in word:
6            count += 1
7    return count

ℹ

Complexity note: This complexity is due to the time taken to create a set of unique patterns (O(n)) and the substring search in the word (O(m)).

1Using a set can reduce the number of checks needed if there are duplicate patterns.
2Built-in substring search functions are optimized and can save time compared to manual checks.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.