#591

Hard

auto_awesomeStack-based state management

LeetCode Problem Workspace

Tag Validator

The Tag Validator problem involves validating a code snippet by parsing through tags using a stack-based state management approach.

string stack

Problem Statement

Given a string representing a code snippet, you are tasked with implementing a tag validator to verify if it is valid based on specific rules. The code must be parsed to identify if tags are properly opened and closed, and whether the content inside these tags follows the given constraints. The snippet is considered valid only if all tags and their contents are properly structured.

The code snippet consists of tags that are enclosed within < > and can contain text, comments, or CDATA sections. The validator must handle nested tags, unbalanced tags, and CDATA content, which might contain invalid tag names but should be treated as plain text. The challenge is to correctly parse through this structure using a stack-based approach.

Examples

Example 1

Input: code = " This is the first line ]]> "

Output: true

The code is wrapped in a closed tag : and . The TAG_NAME is valid, the TAG_CONTENT consists of some characters and cdata. Although CDATA_CONTENT has an unmatched start tag with invalid TAG_NAME, it should be considered as plain text, not parsed as a tag. So TAG_CONTENT is valid, and then the code is valid. Thus return true.

Example 2

Input: code = " >> ![cdata[]] ]>]]>]]>>] "

Output: true

We first separate the code into : start_tag|tag_content|end_tag. start_tag -> " " end_tag -> " " tag_content could also be separated into : text1|cdata|text2. text1 -> ">> ![cdata[]] " cdata -> " ]>]]>", where the CDATA_CONTENT is " ]>" text2 -> "]]>>]" The reason why start_tag is NOT " >>" is because of the rule 6. The reason why cdata is NOT " ]>]]>]]>" is because of the rule 7.

Example 3

Input: code = " "

Output: false

Unbalanced. If " " is closed, then " " must be unmatched, and vice versa.

Constraints

1 <= code.length <= 500
code consists of English letters, digits, ' ', '/', '!', '[', ']', '.', and ' '.

Solution Approach

Stack-Based Parsing

The solution to the Tag Validator problem revolves around stack-based state management. By using a stack, you can handle nested tags and ensure that each tag is properly closed in the correct order. The key to solving this problem is managing the transition between start tags, end tags, and CDATA content.

Handling CDATA Sections

CDATA sections within the code should be treated as plain text, not parsed as tags. The stack-based approach must differentiate between valid tags and CDATA content, ensuring that the CDATA section is skipped in terms of tag validation but still handled correctly within the structure.

Efficient Parsing

To ensure the solution is efficient, the code must be parsed in linear time, maintaining the stack state as you move through the input. Each transition in the tag structure must be managed efficiently to validate the tags, and the space complexity should remain manageable at O(n).

Complexity Analysis

Metric	Value
Time	Regular Expressions are/can be implemented in the form of finite-state machines
Space	O(n)

The time complexity of the solution is O(n), as we parse through the string in a single pass, handling each character once. The space complexity is O(n) because we use a stack to manage tag states, and the maximum size of the stack will be proportional to the number of nested tags in the worst case.

What Interviewers Usually Probe

Look for an understanding of stack-based state management and how it applies to nested tag parsing.
Expect the candidate to handle edge cases like unbalanced tags and CDATA sections.
The candidate should efficiently manage space and time complexity while maintaining correct validation logic.

Common Pitfalls or Variants

Common pitfalls

Mismanaging CDATA sections by treating them as regular tags, leading to incorrect validation.
Failing to properly close tags or mismatching start and end tags, causing the solution to return an incorrect result.
Not efficiently handling nested tags or not using the stack effectively to track tag states.

Follow-up variants

Instead of using a stack, implement the solution using a recursive approach to track the opening and closing of tags.
Handle different tag formats or allow for more complex tag content within the code.
Extend the problem to handle other types of embedded content, such as script tags or special HTML entities.

FAQ

What is the stack-based state management pattern in Tag Validator?

In the Tag Validator problem, stack-based state management is used to track the opening and closing of tags. Each time a start tag is encountered, it is pushed onto the stack, and each time an end tag is encountered, it is popped from the stack. This ensures tags are balanced and nested correctly.

How do CDATA sections affect the Tag Validator solution?

CDATA sections are treated as plain text in the Tag Validator problem. They are skipped in terms of tag validation, but the surrounding text must be properly handled by the stack. This prevents false positives or negatives in validation.

What are some common mistakes in solving Tag Validator?

Common mistakes include failing to handle unbalanced tags, incorrectly parsing CDATA sections as tags, and not properly managing the stack for nested structures.

How does stack-based parsing help with validating tags?

Stack-based parsing helps track the nested structure of tags by pushing start tags onto the stack and popping them when their corresponding end tag is found. This ensures tags are correctly opened and closed in the right order.

What is the space complexity of the Tag Validator solution?

The space complexity of the Tag Validator solution is O(n), as the stack may grow in size proportional to the number of nested tags in the input string.

terminal

Solution

Solution 1

#### Python3

class Solution:
    def isValid(self, code: str) -> bool:
        def check(tag):
            return 1 <= len(tag) <= 9 and all(c.isupper() for c in tag)

        stk = []
        i, n = 0, len(code)
        while i < n:
            if i and not stk:
                return False
            if code[i : i + 9] == '<![CDATA[':
                i = code.find(']]>', i + 9)
                if i < 0:
                    return False
                i += 2
            elif code[i : i + 2] == '</':
                j = i + 2
                i = code.find('>', j)
                if i < 0:
                    return False
                t = code[j:i]
                if not check(t) or not stk or stk.pop() != t:
                    return False
            elif code[i] == '<':
                j = i + 1
                i = code.find('>', j)
                if i < 0:
                    return False
                t = code[j:i]
                if not check(t):
                    return False
                stk.append(t)
            i += 1
        return not stk

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