Improved DSA skills on LeetCode with Java

🚀 Day-65 of #100DaysOfCodeChallenge Today’s problem: 2011. Final Value of Variable After Performing Operations (LeetCode - Easy) This problem was a great reminder that even simple-looking tasks can strengthen our logical reasoning and problem-solving mindset. 🧩 Problem Summary: We’re given a list of operations (++X, X++, --X, X--) that either increment or decrement a variable X. The variable starts at 0, and we need to find its final value after performing all operations on LeetCode. It sounds straightforward — but the beauty of such problems lies in their simplicity. They teach us to: Pay attention to small details. Write clean, efficient logic. Think systematically about every operation in a sequence. 💡 My Approach: I used a simple Java loop to traverse through each operation: If the operation contains '+', increment the value. If it contains '-', decrement it. It’s a one-pass solution — both time and space efficient. ⚙️ Language: Java ⚡ Runtime: 1 ms (Beats 74.53%) 💾 Memory: 42.28 MB (Beats 99.47%) ✅ Status: Accepted (259 / 259 test cases passed) Every solved problem adds one more brick to the wall of consistency and confidence. It’s not just about solving — it’s about understanding, improving, and building the habit of learning every single day. 🔹 Small progress, done daily, creates massive results over time. Onward to Day 66 💪 #100DaysOfCode #LeetCode #CodingJourney #Java #ProblemSolving #TechLearning #DeveloperLife #Consistency #LearningEveryday #ChallengeYourself

🚀 Day 23 of #50DaysLeetCodeChallenge Problem: Binary Search (LeetCode 704) — a timeless classic that reminded me how elegance in programming often lies in simplicity. 🎯 🧠 Thought Process: When dealing with sorted data, you don’t need to search everything — just guide your logic efficiently. Binary Search embodies this idea perfectly: divide, compare, and conquer. It’s all about making smarter moves, not more moves. ⚙️ Approach: 🔹 Initialized two pointers — low and high — to define the search boundaries. 🔸 Calculated the midpoint each time and compared it with the target. 🔹 Adjusted the range intelligently, narrowing down until the target was found (or confirmed missing). 🔸 Returned the index if found, else -1. 📊 Efficiency: ✅ Time Complexity: O(log n) ✅ Space Complexity: O(1) ⏱️ Runtime: 0 ms — Beats 100% of Java submissions! ⚡ 💭 Key Takeaway: Binary Search teaches that speed isn’t always about doing more work, but about doing the right work. It’s a clear reminder that logic and precision go hand in hand when optimizing performance. 💫 Big thanks to Trainer Shishir chaurasiya and PrepInsta for constantly fueling my journey toward sharper logic and smarter problem-solving! 🚀 #LeetCode #Day23 #50DaysOfCode #ProblemSolving #Java #AlgorithmDesign #BinarySearch #CodingChallenge #PrepInsta #DSA #TechLearning #LogicBuilding #DeveloperJourney #ProgrammingLife #CodingLife

📌 Day 20 | #45DaysOfLeetCode Challenge🚀 🔹Another productive day in my continuous learning journey toward mastering Data Structures and Algorithms! 💪 🧩 Problem Solved: Valid Parentheses (LeetCode #20) 💻 Language Used: Java 📈 Status: Accepted ✅ 🔗link:https://lnkd.in/dutDPZdy 🔹This problem might look simple, but it’s a brilliant test of logic, order, and accuracy. The goal was to determine if a string containing various types of brackets (), {}, and [] is valid. 🌱To solve it, I implemented a Stack-based approach, ensuring that: 1️⃣ Each opening bracket is correctly matched with its corresponding closing one. 2️⃣ The order of brackets remains consistent and valid. 3️⃣ No unmatched or misplaced brackets exist in the final string. This exercise strengthened my understanding of: 🔹 LIFO (Last In, First Out) principles. 🔹 Stack operations in Java. 🔹 Real-world logic validation techniques. 🧠 Writing this logic made me appreciate how even small syntax patterns mirror real-world programming reliability — one wrong match can break an entire flow! 📊 Performance Stats: ⏱️ Runtime: 4 ms (Beats 29.38%) 💾 Memory: 43.26 MB (Beats 10.60%) 🌱 Every new challenge enhances my ability to think structurally and code efficiently. I’m not just solving problems — I’m improving the way I approach them. 🔹Consistent practice, structured thinking, and persistence are shaping me into a stronger Java developer every single day 🚀 #Day20 #LeetCode #100DaysOfCode #JavaDeveloper #ProblemSolving #DataStructures #CodingJourney #WomenInTech #DeveloperGrowth #SoftwareEngineering #IT #Dream #LearningNeverStops #AchieveMyGoal

Finished a fun little challenge: a **Tip Calculator**! 💸 The requirement wasn't just to calculate the tip, but to handle messy inputs (like `"$10.00"` and `"25%"`) and ensure the output was perfectly formatted to currency standards (like `"$2.50"`). The most effective solutions start with clean data. I used two key Python techniques to handle the required formatting and calculation in the most efficient way possible: 1.  **Input Cleaning:** Simple `.replace()` calls were used to strip the dollar sign and percent sign, immediately converting the strings into usable `float` values. 2.  **Pythonic Output:** The final output is handled in a single, powerful **list comprehension**. This not only calculates all three tips (15%, 20%, and custom) but uses a precise **f-string format specification** (`:.2f`) to guarantee the correct currency format and two-decimal rounding. This avoids messy loops and redundant code! This approach ensures the code is accurate, fast, and extremely readable. The core logic is contained in one concise line: ```python def calculate_tips(meal_price: str, custom_tip: str) -> list[str]:     # ... Input cleaning ...         # List comprehension calculates all tips and formats the output string     return [         f"${round(tip_amount, 2):.2f}"         for tip_amount in [price * 0.15, price * 0.20, price * percent_custom]     ] ``` When solving challenges, do you prefer solving calculation and formatting in one step (like this list comprehension) or breaking them into separate loops? Share your preference below! Find the full, clean code on my GitHub: https://lnkd.in/g-C9ymiM Go to freeCodeCamp's daily coding challege to solve it yourself. While you're there checkout their Certified Full Stack Developer Curriculum: https://lnkd.in/g7i6Tc5s #Python #ListComprehension #Fstrings #DataCleaning #CodingChallenge #SoftwareDevelopment

Progressing through boot.dev, I had to laugh at myself. I was joking with a friend who is a full-time developer about my limited experience in coding/scripting. I jokingly said I never saw a problem I couldn't solve with a bash script and a bunch of if/then/else statements. I got this question correct, but when I checked the expert solution, I had to chuckle: " Assignment: Complete the player_1_wins function. It should return True if player 1 has a higher score, and False otherwise. " I still love a good if/else because it matches the way my brain iterates through problems: a mental flowchart/decision tree. I still have a lot to learn, and this is what I think the value in platforms like boot.dev or Codecademy really is. I've done a fair bit of "coding," making one-off Python or Bash scripts using tools like sed, awk, and grep to help me do things like look for info in huge log sets or recursively extract log sets that mix compression types (.tar/.GZ/.ZIP). Sometimes a .tar.gz with a .zip inside with another .tar inside that, and so on. And there is value in my method of "just make something" but having the guided lessons and problem sets and the ability to look at how someone else with a lot of experiance would solve that is a huge win. You can gain experiance and wisdom concurently. My answer is on the left, the expert's is on the right.

When I first started learning Java, I thought it was just another programming language. But soon, I realized it’s more than syntax — it’s about problem-solving, logic, and structured thinking. That’s what led me to dive deep into Data Structures & Algorithms (DSA). Every problem I solve teaches me something new — not just about code, but about how to think. Here’s what I’m building along the way: 💡 Analytical thinking — breaking complex problems into smaller, solvable steps. 🧠 Consistency — solving even one problem a day compounds over time. 💬 Communication — learning to explain logic clearly is as important as writing the code. ⚙️ Resilience — debugging teaches patience better than anything else. I may not be a coding expert yet — but I’m becoming 1% better every day. Because success isn’t a leap; it’s a series of small, intentional steps. 🌟 Goal: Master DSA in Java and build scalable real-world projects that make an impact. 💬 How are you investing in your skills today for tomorrow’s success? #Java #DSA #LearningJourney #CodingMindset #CareerGrowth #Consistency #StudentDeveloper #ProblemSolving #InvertisCreators #InvertisLinkedInSummit

Day 26 of #50DaysLeetCodeChallenge 🧩 Problem: 561. Array Partition Today’s problem was a refreshing one — an Easy-level LeetCode challenge that reinforces how sorting and pairing can optimize outcomes. It’s one of those problems that looks simple but beautifully demonstrates the power of greedy algorithms. 🧠 Thought Process: 🔹 The task is to group integers into pairs such that the sum of the smaller element in each pair is maximized. 🔹 Sorting the array ensures each pair is as balanced as possible. 🔹 Once sorted, we simply take every alternate element (starting from index 0), since that will always represent the smaller element in each optimal pair. 🔹 This method eliminates unnecessary complexity and ensures maximum total sum. ⚙️ My Approach: 🔸 Sort the array using Arrays.sort(nums). 🔸 Initialize sum = 0. 🔸 Loop through the array with a step of 2, adding nums[i] to the sum each time. 🔸 Return the final sum — the maximum possible result. 📈 Performance: ✅ Accepted ⚡ Runtime: 17 ms (Beats 13.97%) 💾 Memory: Efficient and clean implementation 💡 Reflection: Sometimes, simplicity is the key to optimization. Even without complex data structures, understanding the problem’s core logic can lead to elegant solutions. Each day’s challenge sharpens both reasoning and coding clarity. Grateful to Trainer Shishir chaurasiya and PrepInsta for guiding me through consistent, concept-driven learning in DSA 🙏 #LeetCode #50DaysLeetCodeChallenge #ProblemSolving #Java #AlgorithmDesign #CodingChallenge #PrepInsta #DeveloperJourney #LogicBuilding #DSA #CleanCode #LearningEveryday

𝗪𝗵𝗲𝗻 𝗜 𝘀𝘁𝗮𝗿𝘁𝗲𝗱 𝗰𝗼𝗹𝗹𝗲𝗴𝗲, 𝗼𝗻𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗸𝗲𝗽𝘁 𝗯𝗼𝘁𝗵𝗲𝗿𝗶𝗻𝗴 𝗺𝗲: “𝘚𝘩𝘰𝘶𝘭𝘥 𝘐 𝘥𝘰 𝘋𝘢𝘵𝘢 𝘚𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦𝘴 & 𝘈𝘭𝘨𝘰𝘳𝘪𝘵𝘩𝘮𝘴 (𝘋𝘚𝘈) 𝘪𝘯 𝘑𝘢𝘷𝘢 𝘰𝘳 𝘊++?” 🤔 At that time, it felt like choosing the right language would make all the difference. And honestly, I overthought it a lot 😅 But as I started learning, I realised something important — ➡️ 𝗜𝘁’𝘀 𝗻𝗼𝘁 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲, 𝗶𝘁’𝘀 𝗮𝗯𝗼𝘂𝘁 𝗹𝗼𝗴𝗶𝗰 𝗮𝗻𝗱 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀. The language is just a tool — your ability to solve problems is what truly matters. Still, for anyone stuck with this question right now, here are a few thoughts from my own experience 👇 🔹 𝗖++ ✅ Shorter syntax — great for competitive programming. ✅ The STL (Standard Template Library) is a game-changer for quick and efficient coding. ⚙️ Helps you understand how memory and data structures actually work under the hood. 🔹 𝗝𝗮𝘃𝗮 ✅ A bit more verbose, but very structured — improves readability and debugging. ✅ Once you grasp Java, learning other development languages (like Kotlin, C#, etc.) feels natural. ✅ Excellent for Object-Oriented Programming and backend development. 💡 My takeaway: Start with whichever language you’re comfortable in — just stay consistent. You can learn a new language in weeks, but mastering logic, time complexity, and problem-solving patterns takes patience and practice. So pick one, stay consistent, and keep solving 🚀 #DSA #Programming #Java #Cpp #CodingJourney #StudentCommunity #TechLearning #ProblemSolving #MITManipal

💻🚀 From Learning to Building – The Real Beginning Every big journey starts with one small spark of curiosity. 🌱 After exploring how transformation feels, I’m now diving into how it truly works — technically. This is where my developer journey begins — where Java logic turns into working systems, and backend connects everything. 💡 Here’s what’s powering my growth right now 👇 🔹 Languages & Frameworks: Java, Spring Boot, MySQL 🔹 Core Concepts: OOPs, Collections, Exception Handling, RESTful APIs 🔹 Tools I Use Daily: IntelliJ IDEA, Postman, MySQL Workbench, Git & GitHub 🔹 Learning Resources: – Apna College – OOPs with Java → https://lnkd.in/gsbBf84n – GeeksforGeeks – Problem Solving & DSA → https://lnkd.in/gguwPMvk – Smart Programming – Notes by Deepak Sir → https://lnkd.in/dvu5dEQf – Code With Harry – Java Roadmap to Start → https://lnkd.in/ga_4n_nn – WsCube Tech – API Development Tutorials → https://lnkd.in/gkX2HBMb 💫 Over the next few posts, I’ll share: How I build and test APIs using Spring Boot How backend logic connects with frontend flow How database design impacts performance And my go-to learning resources that make learning practical & consistent This isn’t just documentation — it’s a journey of learning, logic, and evolution. Because transformation doesn’t end when you understand — it begins when you build. ⚙️✨ #javadeveloper #backenddeveloper #springboot #mysql #restapi #learningjourney #growthmindset #fromlearningtobuilding #softwaredevelopment #womenintech #smartprogramming #codewithharry #apnacollege #wscubetech