LeetCode #3374 — HARD

First Letter Capitalization II

Break down a hard problem into reliable checkpoints, edge-case handling, and complexity trade-offs.

Solve on LeetCode
The Problem

Problem Statement

Table: user_content

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| content_id  | int     |
| content_text| varchar |
+-------------+---------+
content_id is the unique key for this table.
Each row contains a unique ID and the corresponding text content.

Write a solution to transform the text in the content_text column by applying the following rules:

  • Convert the first letter of each word to uppercase and the remaining letters to lowercase
  • Special handling for words containing special characters:
    • For words connected with a hyphen -, both parts should be capitalized (e.g., top-rated → Top-Rated)
  • All other formatting and spacing should remain unchanged

Return the result table that includes both the original content_text and the modified text following the above rules.

The result format is in the following example.

Example:

Input:

user_content table:

+------------+---------------------------------+
| content_id | content_text                    |
+------------+---------------------------------+
| 1          | hello world of SQL              |
| 2          | the QUICK-brown fox             |
| 3          | modern-day DATA science         |
| 4          | web-based FRONT-end development |
+------------+---------------------------------+

Output:

+------------+---------------------------------+---------------------------------+
| content_id | original_text                   | converted_text                  |
+------------+---------------------------------+---------------------------------+
| 1          | hello world of SQL              | Hello World Of Sql              |
| 2          | the QUICK-brown fox             | The Quick-Brown Fox             |
| 3          | modern-day DATA science         | Modern-Day Data Science         |
| 4          | web-based FRONT-end development | Web-Based Front-End Development |
+------------+---------------------------------+---------------------------------+

Explanation:

  • For content_id = 1:
    • Each word's first letter is capitalized: "Hello World Of Sql"
  • For content_id = 2:
    • Contains the hyphenated word "QUICK-brown" which becomes "Quick-Brown"
    • Other words follow normal capitalization rules
  • For content_id = 3:
    • Hyphenated word "modern-day" becomes "Modern-Day"
    • "DATA" is converted to "Data"
  • For content_id = 4:
    • Contains two hyphenated words: "web-based" → "Web-Based"
    • And "FRONT-end" → "Front-End"

Constraints:

  • context_text contains only English letters, and the characters in the list ['\', ' ', '@', '-', '/', '^', ',']

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: Table: user_content +-------------+---------+ | Column Name | Type | +-------------+---------+ | content_id | int | | content_text| varchar | +-------------+---------+ content_id is the unique key for this table. Each row contains a unique ID and the corresponding text content. Write a solution to transform the text in the content_text column by applying the following rules: Convert the first letter of each word to uppercase and the remaining letters to lowercase Special handling for words containing special characters: For words connected with a hyphen -, both parts should be capitalized (e.g., top-rated → Top-Rated) All other formatting and spacing should remain unchanged Return the result table that includes both the original content_text and the modified text following the above rules. The result format is in the following example.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: General problem-solving

Example 1

{"headers":{"user_content":["content_id","content_text"]},"rows":{"user_content":[[1,"hello world of SQL"],[2,"the QUICK-brown fox"],[3,"modern-day DATA science"],[4,"web-based FRONT-end development"]]}}
Step 02

Core Insight

What unlocks the optimal approach

  • No official hints in dataset. Start from constraints and look for a monotonic or reusable state.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Largest constraint values
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #3374: First Letter Capitalization II
// Auto-generated Java example from py.
class Solution {
    public void exampleSolution() {
    }
}
// Reference (py):
// # Accepted solution for LeetCode #3374: First Letter Capitalization II
// import pandas as pd
// 
// 
// def capitalize_content(user_content: pd.DataFrame) -> pd.DataFrame:
//     def convert_text(text: str) -> str:
//         return " ".join(
//             (
//                 "-".join([part.capitalize() for part in word.split("-")])
//                 if "-" in word
//                 else word.capitalize()
//             )
//             for word in text.split(" ")
//         )
// 
//     user_content["converted_text"] = user_content["content_text"].apply(convert_text)
//     return user_content.rename(columns={"content_text": "original_text"})[
//         ["content_id", "original_text", "converted_text"]
//     ]
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n)
Space
O(1)

Approach Breakdown

BRUTE FORCE
O(n²) time
O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED
O(n) time
O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.