Next Permutation Algorithm in 22 Days of Code with Educative

Day 30 of #30DaysOfCode with Educative Challenge: Continuous Subarray Sum (Medium) Core Idea: Detect a subarray whose sum is a multiple of a given number The Pattern: Running total with remainder tracking Why It Works Here: Keep a running total while walking through the array and record the first position where each remainder (after dividing by the given number) appears. When the same remainder shows up again at least two positions later, it means the numbers between those two positions add up to a value that fits the requirement. Production Lesson: This pattern is useful whenever repeated “states” over a stream need to be detected quickly. Log analysis, rolling counters, or anomaly detection can often be reduced to tracking how cumulative values repeat over time instead of re-scanning all ranges. Edge Worth Remembering: Storing an initial remainder state at a virtual index before the array starts allows subarrays beginning at the first element to be handled cleanly. #Educative #Python #SoftwareEngineering #ContinuousLearning #ProblemSolving

Day 29 of #30DaysOfCode with Educative Challenge: Palindrome Number (Easy) Core Idea: Check symmetry from both ends The Pattern: Two-pointer scan toward the center Treat the number as a string, compare the leftmost and rightmost characters, and move both pointers inward until they cross or a mismatch appears. Why It Works Here: A palindrome reads the same forward and backward, so matching pairs at symmetric positions is enough to confirm validity without building a reversed copy or doing extra work. Production Lesson: This simple two-pointer pattern shows up in many real checks on IDs, tokens, or formatted strings. Validations can often be done by local comparisons rather than reconstructing entire structures. Edge Worth Remembering: Early exit on the first mismatch avoids unnecessary comparisons and keeps the solution efficient even for longer inputs. #Educative #Python #SoftwareEngineering #ContinuousLearning #ProblemSolving

𝗗𝗦𝗔 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 - 𝟲/𝟯𝟬 Continuing daily DSA practice by focusing on a core sliding window problem and ensuring a clear understanding of the approach. 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝗼𝗹𝘃𝗲𝗱 (𝗟𝗲𝗲𝘁𝗖𝗼𝗱𝗲 - 𝗠𝗲𝗱𝗶𝘂𝗺): 1️⃣ 𝗟𝗼𝗻𝗴𝗲𝘀𝘁 𝗦𝘂𝗯𝘀𝘁𝗿𝗶𝗻𝗴 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗥𝗲𝗽𝗲𝗮𝘁𝗶𝗻𝗴 𝗖𝗵𝗮𝗿𝗮𝗰𝘁𝗲𝗿𝘀 • Approach: Sliding Window using two pointers and a set • Key Takeaway: Shrinking the window when duplicates appear maintains a valid substring in linear time. Focused on correctness and understanding how window expansion and contraction work together. #DSA #Python #LeetCode #ProblemSolving

Day 30/50 – DSA Problem-Solving Challenge Problem: Maximize Revenue from Video Streams with Bandwidth Limit Concepts: Greedy Algorithm | Fractional Knapsack | Sorting Difficulty: Medium Optimized Approach (Greedy): - Compute revenue per MB (density) for each stream - Sort streams in descending order of density - Allocate bandwidth to the most profitable streams first - Take fractional bandwidth when full allocation is not possible - Stop when bandwidth is exhausted Key Learnings: - Greedy choice works when fractional selection is allowed - Sorting by value per unit is more effective than sorting by size or value alone - Fractional Knapsack guarantees optimal results Consistently practicing DSA to strengthen problem-solving skills. Github link: https://lnkd.in/diUtbyXb #Day30 #DSA #GreedyAlgorithm #FractionalKnapsack #Python #ProblemSolving #LearningInPublic #CodingJourney #InterviewPrep

🚀 𝟲𝟬 𝗗𝗮𝘆𝘀 𝗼𝗳 𝗖𝗼𝗱𝗶𝗻𝗴 | 𝗗𝗦𝗔 𝘅 𝗥𝗲𝗮𝗹 𝗪𝗼𝗿𝗹𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 #Day34 | 𝗖𝗼𝘂𝗿𝘀𝗲 𝗣𝗿𝗲𝗿𝗲𝗾𝘂𝗶𝘀𝗶𝘁𝗲 𝗣𝗹𝗮𝗻𝗻𝗲𝗿 Built a Course Prerequisite Planner using Topological Sort (Kahn’s Algorithm) to resolve course dependencies and generate a valid completion order. Focused on: • Directed graphs • Indegree-based processing • Cycle detection • Understanding how dependency resolution works in real systems 📌 𝗖𝗼𝗱𝗲 𝗮𝗻𝗱 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: https://lnkd.in/gxzGJ4nB Feedback and suggestions are welcome. #DSA #Graphs #TopologicalSort #Dependencies #Python #60DaysOfCoding #LearningInPublic #SoftwareEngineering

🚀 DSA Practice – Daily Progress 📌 Problem: Sort an array of 0s, 1s, and 2s (without using built-in sort) Today I solved a classic DSA problem using the Dutch National Flag algorithm. 🔍 Approach: Used three pointers (low, mid, high) Segregated 0s, 1s, and 2s in a single pass Achieved in-place sorting with constant extra space ⏱ Complexity: Time: O(n) Space: O(1) 📖 Key Takeaway: Simple pointer-based greedy strategies can lead to highly efficient solutions when constraints are well understood. #DSA #ProblemSolving #Python #Algorithms #CodingPractice #GeeksforGeeks #LearningJourney

365 Days of DSA – #Day212: Longest Happy Prefix 🔁🧵 Today’s challenge was to find the longest prefix of a string that is also a suffix (excluding the full string itself). I approached it by comparing growing prefixes with shrinking suffixes and keeping track of the longest valid match found. While straightforward, this problem highlights how string comparisons can quickly become expensive — and why more optimized techniques (like KMP) are often preferred for larger inputs. A good exercise in understanding string boundaries and overlaps. #Day212 #365DaysOfDSA #Strings #PrefixSuffix #LeetCode #Python #ProblemSolving #DSA #CodingChallenge

💯 Day 71 / 100 – 100 Days of #LeetCode Challenge 🔁 🧩 Problem: 1863. Sum of All Subset XOR Totals You are given an array of integers. For every possible subset of the array, compute the bitwise XOR of its elements, and return the sum of all these XOR values. ✅ Approach: Bitwise Insight Instead of generating all subsets (which would be exponential), we can use a bitwise observation: Each element contributes to the XOR total in exactly half of all subsets. Taking the bitwise OR of all elements captures every bit that can appear in subset XORs. Multiply this combined value by 2ⁿ⁻¹, where n is the number of elements. This gives the final result efficiently without explicitly forming subsets. 📊 Complexity Time: O(n) Space: O(1) 💡 Key Takeaway This problem shows how understanding bitwise patterns can transform an exponential problem into a linear-time solution. Recognizing contribution frequency is a powerful trick in combinatorics and bit manipulation problems. #100DaysOfLeetCode #Day71 #BitManipulation #LeetCode #CodingChallenge #ProblemSolving #DSA #Algorithms #Python #TechJourney #LearningEveryday #CodingLife

✨ Day 69 of #100DaysOfDSA 📌 LeetCode 961: N-Repeated Element in Size 2N Array A neat problem that highlights how problem constraints can guide us to an optimal solution. 🧩 Problem Insight: The array has 2n elements Only one element repeats n times The rest appear exactly once 🧠 Approach & How It Works: Use a hash set to track visited elements Traverse the array once The first element that appears again must be the answer due to the given constraints ⚡ This guarantees a single-pass solution with immediate detection. ⚙️ Performance: 🚀 Runtime: 0 ms (beats 100%) 📦 Memory: 13.28 MB (beats 85.16%) ✅ Testcases Passed: 103 / 103 📘 What I Learned: ✔ Leveraging problem constraints for faster solutions ✔ Efficient use of hash sets ✔ Writing clean O(n) time complexity code ✔ Early exit strategies for optimization Consistency > Motivation. One problem at a time 💪 #LeetCode #DSA #Array #RepeatedElements #100DaysOfDSA #100DaysOfCode #Python #ProblemSolving #CodingPractice #TechJourney

🚀 DSA Practice – Daily Progress 📌 Problem: Detect Redundant Parentheses in a Balanced Expression Solved a stack-based problem today to check whether a given mathematical expression contains redundant parentheses. 🔍 Approach: Used a stack to process the expression character by character On encountering a closing bracket ), checked whether the sub-expression inside contained any operator If no operator was found, the parentheses were marked as redundant ⏱ Complexity: Time: O(n) Space: O(n) 📖 Key Takeaway: Stack-based solutions are extremely effective for expression validation problems and help in identifying unnecessary structures efficiently. #DSA #ProblemSolving #Stacks #Python #Algorithms #CodingPractice #GeeksforGeeks #LearningJourney