When to Avoid Java Streams for Performance

🎯 Day 62 of #100DaysOfLeetCode Today I solved the “Merge Two Sorted Lists” problem using Java This problem is a great exercise in understanding how to work with Linked Lists and pointer manipulation. The goal is to merge two sorted linked lists into one sorted list — without using extra space for another list. Key Concepts Practiced: Linked List traversal Dummy node technique Efficient merging using pointers Handling null edge cases Approach Summary: Create a dummy node to simplify edge cases. Use two pointers to traverse both lists. Compare values and link nodes in sorted order. Attach any remaining nodes at the end. #100DaysOfCode #LeetCode #Java #CodingChallenge #DataStructures #LinkedList #ProblemSolving #SoftwareEngineering

🧠 Why I stopped overusing Java Streams When Java Streams appeared, I was amazed. One line instead of a dozen loops? Beautiful. But over time, I realized: beauty ≠ efficiency. Streams are great for readability — until they aren’t. Nested streams, multiple filters, and maps can easily hide complexity and create unnecessary object allocations. In high-load systems, that’s a silent killer. Sometimes a simple for loop performs 3–4x faster — and is much easier to debug. 👉 My rule now: Use Streams when they make code clearer, not just shorter. Write for humans first, not compilers. #Java #BackendDevelopment #CodeQuality #ProgrammingTips #SoftwareEngineering

💡 Java Collections — Under the Hood Understanding how collections work = writing faster, efficient code. 🔹 HashMap → Key-value, hash buckets + tree structure (since Java 8) 🔹 HashSet → Built on HashMap 🔹 ArrayList → Dynamic resizing arrays 🔹 LinkedList → Doubly linked nodes 🔹 TreeMap → Red-black tree sorted by key Master these, and performance tuning becomes instinctive ⚙️ 💬 Which one do you use most often — and why? #Java #DataStructures #Coding #SystemDesign #BackendDevelopment

💻 Day 45 of #LeetCode Journey 🚀 ✅ Problem: Count and Say 📘 Language: Java 🔹 Status: Accepted (30/30 test cases passed) 🔹 Runtime: 4 ms | Beats 55.38% 🔹 Memory: 41.86 MB 🧠 Concept: This problem is about generating the n-th term in the “count and say” sequence. Each term is built by describing the previous term — count the number of digits and say them in order. 🧩 Approach: Start with "1". For each iteration, use a StringBuilder to construct the next sequence. Track consecutive digits using a counter. Append the count and digit when the sequence changes. 💡 Efficient string manipulation and iteration give optimal performance. 🔥 Every solved problem builds confidence. One step closer to mastering patterns in strings! #Day45 #LeetCode #Java #CodingChallenge #ProblemSolving #CountAndSay #50DaysOfCode

#Day-68) LeetCode #3228 – Maximum Number of Operations to Move Ones to the End (Java Edition) Tackled this neat string problem using a greedy approach in Java. The challenge? Move '1's to the end of the string under specific movement rules, maximizing the number of valid operations. 🧠 Core Idea: Track how many '0's we've seen and how many '1's we've already moved. Only move a '1' if there's enough '0's to justify it and the next character is also '1'. 💻 Java Strategy: Loop through the string Use counters to manage '0's and '1's Let me know how you'd tweak this or if you see a more optimal path! #Java #LeetCode #GreedyAlgorithm #StringProblems #DSA #CodingChallenge #LinkedInTech #ProblemSolving

💡𝗝𝗮𝘃𝗮 𝗧𝗶𝗽/𝐒𝐩𝐫𝐢𝐧𝐠 𝐁𝐨𝐨𝐭 𝐓𝐢𝐩 - 𝗜𝗻𝘀𝘁𝗮𝗻𝗰𝗲𝗼𝗳 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 𝗠𝗮𝘁𝗰𝗵𝗶𝗻𝗴 🔥 💎 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗶𝘁? Pattern matching with instanceof (Java 16+) lets you test an object's type AND declare a new variable in one step. When the pattern matches, the variable is automatically cast and assigned. This eliminates redundant casting and makes your code more concise. ✅ 𝗞𝗲𝘆 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 ◾ Combines type checking and variable declaration in a single expression. ◾ Eliminates explicit casting and reduces boilerplate code. ◾ Prevents ClassCastException with compile-time safety. ⚡ 𝗖𝗼𝗺𝗺𝗼𝗻 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 ◾ Type checking in if statements: if (obj instanceof String str). ◾ Switch expressions with pattern matching (Java 21+). ◾ Processing collections with different element types. 🤔 Do you use pattern matching in your code? #java #springboot #programming #softwareengineering #softwaredevelopment

✅ Day 57/100 — LeetCode Challenge Problem: Transpose Matrix Language: Java Today I worked on a classic matrix operation — transposing a matrix. The goal is to convert rows into columns and vice-versa. This problem reinforced my understanding of 2D arrays and index manipulation in Java. 💡 Key Idea: If matrix has dimensions m x n, the transpose will have dimensions n x m, and each element at (i, j) becomes (j, i). 📌 Approach: Calculate row & column length Create result matrix with swapped dimensions Iterate & swap positions accordingly #100DaysOfCode #LeetCode #Java #DSA #Matrix #TechJourney #CodingChallenge #SoftwareEngineering #LearningEveryday

Week 8 || Day 2💡 Reversing words in Java — step by step! Today I practiced reversing each word in a sentence using two different approaches: 🔹 Approach 1 — With .reverse() method: Split the sentence using split(" ") to separate words. Used StringBuffer for each word and applied .reverse() directly. Joined the reversed words back with spaces. 🔹 Approach 2 — Without using .reverse(): Again split the string into words. For each word, used a for loop running from the last character to the first. Appended each character manually into a new StringBuffer. Combined the reversed words carefully, avoiding extra spaces.⚡ #Java #StringBuffer #ProgrammingLogic #JavaFullStack

💥 “𝘛𝘩𝘪𝘯𝘬 𝘊𝘰𝘭𝘭𝘦𝘤𝘵𝘪𝘰𝘯𝘴.𝘴𝘰𝘳𝘵() 𝘪𝘴 𝘢𝘭𝘭 𝘺𝘰𝘶 𝘯𝘦𝘦𝘥? 𝘞𝘢𝘪𝘵 𝘵𝘪𝘭𝘭 𝘺𝘰𝘶 𝘮𝘦𝘦𝘵 𝘊𝘰𝘮𝘱𝘢𝘳𝘢𝘵𝘰𝘳 𝘢𝘯𝘥 𝘊𝘰𝘮𝘱𝘢𝘳𝘢𝘣𝘭𝘦!” Sorting in Java gets really fun when you start adding your own logic. In my latest video, I’ve explained how to sort not just integers — but your custom objects (like students, names, anything!) — using Comparator, Comparable, and Lambda expressions. 📺 Watch the full breakdown here: https://lnkd.in/gkvb2VxY #Java #Programming #Coding #Comparator #Comparable #LearnJava #SoftwareDevelopment

#Day-69) LeetCode 2536: Increment Submatrices by One using a 2D difference array technique in Java — a powerful approach for handling multiple range updates efficiently. 🔧 Instead of brute-force iteration over each query, I used a prefix sum strategy to apply all updates in constant time per query, followed by a cumulative pass to build the final matrix. 🧠 Highlights: Efficient submatrix updates using difference matrix Prefix sum accumulation for final values Clean, scalable Java implementation 📌 This kind of problem is a great reminder: smart preprocessing beats brute force. Let’s connect if you’ve explored similar matrix tricks or want to brainstorm more Java optimizations! #Java #LeetCode #DSA #MatrixOptimization #CodingInPublic #ProblemSolving #TechJourney #LinkedInTech