Day 4 DSA: Container With Most Water Brute + Roman to Integer

TL;DR: Today I tackled Container With Most Water and Roman to Integer problems, focusing on building solid foundations before optimization. Here's what I learned and how you can apply these concepts in technical interviews.

🎯 What HR Recruiters Need to Know About This Post

For Hiring Managers & Technical Recruiters: This post demonstrates:

✅ Problem-solving methodology - I build brute force solutions first, then optimize
✅ Learning agility - Actively researching advanced techniques (Two Pointer method)
✅ Code documentation - All solutions available on GitHub with clear explanations
✅ Consistency - Day 4 of a committed 90-day learning journey
✅ Growth mindset - Acknowledging inefficiencies while planning improvements

📚 Today's Technical Deep Dive

Problem 1: Container With Most Water - The Foundation-First Approach

The Challenge: Find two lines that form a container holding the maximum amount of water.

My Strategy:

Start with Brute Force (O(n²) time complexity)
- Check every possible pair of lines
- Calculate area for each pair
- Track maximum area found

Why Brute Force First?

🧠 Builds logical thinking - Essential for technical interviews
🔍 Reveals edge cases - Helps understand the problem deeply
💡 Interview strategy - Many companies appreciate seeing your thought process

from typing import List

class Solution:
    def maxArea(self, height: List[int]) -> int:
        maxvol = 0  # Stores the maximum area found

        # Try all possible pairs of lines (brute-force approach)
        for i in range(len(height) - 1):
            for j in range(i + 1, len(height)):
                # Water is limited by the shorter line
                minheight = min(height[i], height[j])

                # Width is the horizontal distance between lines
                width = j - i

                # Area = minheight * width
                temp = minheight * width

                # Update max area if current is greater
                maxvol = max(maxvol, temp)

        return maxvol

Next Step: Two Pointer Optimization (O(n) solution)

I'm studying this technique for tomorrow's implementation
This shows progression from basic to advanced solutions

Problem 2: Roman to Integer - Clean String Processing

Key Learning: Dictionary mapping + reverse traversal for handling subtraction cases.

class Solution:
    def romanToInt(self, s: str) -> int:
        # Dictionary to map Roman numerals to their integer values
        roman = {
            'I': 1,
            'V': 5,
            'X': 10,
            'L': 50,
            'C': 100,
            'D': 500,
            'M': 1000
        }

        total = 0         # This will store the final integer result
        prev_value = 0    # Tracks the value of the previous Roman numeral

        # Iterate over the string in reverse (right to left)
        for char in reversed(s):
            value = roman[char]  # Get the integer value of the current Roman numeral

            # If the current value is less than the previous one, we subtract it
            # Example: IV -> 5 (V) comes before 1 (I), so we subtract 1 -> total = 4
            if value < prev_value:
                total -= value
            else:
                # Otherwise, we add it to the total
                total += value

            # Update prev_value to the current one for the next iteration
            prev_value = value

        return total  # Return the final converted integer

🎯 Key Takeaways for Beginners Following This Journey

1. Master the Basics Before Optimization

Brute force solutions show you understand the problem
Optimization comes naturally once logic is solid
Interview tip: Always explain your brute force approach first

2. Time Complexity Matters (But Understanding Matters More)

O(n²) vs O(n) - know the difference
Be ready to discuss trade-offs in interviews
Practice explaining complexity in simple terms

3. Document Your Learning Process

GitHub repository with clean, commented code
Shows continuous learning to potential employers
Helps other developers learn from your journey

📈 Progress Tracking & Metrics

Day 4 Stats:

✅ 2 Problems solved
✅ 1 New technique researched (Two Pointer)
✅ Code documented and pushed to GitHub
✅ Learning methodology refined

Consistency Score: 4/90 days completed (4.4% progress) 🔥

🔗 Resources & Links

GitHub Repository: Day 4 Solutions
Problem Sources: LeetCode, HackerRank
Next Study Topic: Two Pointer Technique Implementation

💼 Why This Matters for Your Career

For Job Seekers:

Demonstrates consistent learning habits
Shows ability to break down complex problems
Proves commitment to technical growth
Documents problem-solving methodology

For Students:

Learn alongside my journey
See real problem-solving in action
Understand interview preparation strategies
Build your own coding discipline

📢 Join My Learning Journey!

Following my #90DaysOfDSA challenge?

⭐ Star my GitHub repository
💬 Share your own solutions in the comments
🔔 Follow for daily updates and insights
📧 Connect with me for collaboration opportunities

For Recruiters: Feel free to reach out - I'm actively seeking ai development opportunities and would love to discuss how my problem-solving approach can benefit your team.

Day 4 complete! Tomorrow we optimize. The journey continues... 💪

Tags: #DSA #DataStructures #Algorithms #TechnicalInterview #SoftwareDeveloper #ProblemSolving #CodingChallenge #JobSearch #Programming #LeetCode #GitHub #CareerGrowth #TechSkills

Day 4: From Brute Force to Optimization - My Data Structures & Algorithms Learning Journey 🚀