How do you solve HTML Entity Parser on LeetCode?

HTML Entity Parser (LeetCode #1410) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Using a mapping for replacements can significantly reduce the complexity.

What is the brute force solution for HTML Entity Parser?

The brute force approach for HTML Entity Parser is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves scanning through the string character by character, looking for the '&' symbol. When found, we check if it forms a valid HTML entity by looking for a subsequent ';'. If it does, we replace it with the corresponding character. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve HTML Entity Parser?

HTML Entity Parser uses the following concepts: Hash Table, String. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for HTML Entity Parser?

Always clarify the problem statement and constraints before jumping into coding. Think about edge cases, such as strings without any entities or strings that are entirely entities. Practice writing clean and efficient code to improve your speed during interviews.

What are common mistakes when solving HTML Entity Parser?

Not handling cases where '&' does not form a valid entity. Overlooking the need to check for the end of the string when searching for entities.

#1410

HTML Entity Parser

Medium

Hash TableStringHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal solution uses a single pass through the string while utilizing a mapping of HTML entities to their corresponding characters. This allows for efficient replacements without needing to check each character multiple times.

⚙️

Algorithm

6 steps

1Step 1: Create a dictionary to map HTML entities to their corresponding characters.
2Step 2: Initialize an empty result string.
3Step 3: Use a while loop to iterate through the input string.
4Step 4: If the current character is '&', check if the next characters form a valid entity using the dictionary.
5Step 5: If a valid entity is found, append the corresponding character to the result string; otherwise, append the original character.
6Step 6: Return the result string.

solution.py28 lines

1# Full working Python code
2
3def entityParser(text):
4    entity_map = {
5        '&quot;': '"',
6        '&apos;': '\',
7        '&amp;': '&',
8        '&gt;': '>',
9        '&lt;': '<',
10        '&frasl;': '/'
11    }
12    result = ''
13    i = 0
14    while i < len(text):
15        if text[i] == '&':
16            for entity in entity_map:
17                if text.startswith(entity, i):
18                    result += entity_map[entity]
19                    i += len(entity)
20                    break
21            else:
22                result += text[i]
23                i += 1
24        else:
25            result += text[i]
26            i += 1
27    return result
28

ℹ

Complexity note: The time complexity is O(n) because we traverse the string once, and the space complexity is O(n) due to the storage of the result string.

1Using a mapping for replacements can significantly reduce the complexity.
2Single-pass algorithms are often more efficient than nested iterations.

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