Day 6 Today, I focused on revisiting key concepts in SQL: 1. Joining multiple tables. 2. ⁠UNION: Union selects only distinct values. 3. ⁠UNION ALL: It includes duplicate values. 4. ⁠UNION with WHERE. 5. ⁠STRING Function: LENGTH, UPPER, LOWER, TRIM. 6. Substring. Consistency beats intensity. Small daily effort compounds into big results. 📌

Day 31/90 🚀 Solved LC 2130 and LC 3 today. Learned how reversing part of a linked list can simplify a problem and how the Sliding Window pattern efficiently handles substring problems. #100DaysOfCode #DSA #LeetCode

One thing to do Sunday: search your approval code for substring operations or CSS ellipsis. If you find it between the user input and the approve button, that's your vulnerability. Fix it before someone finds it for you.

Check approval views for .substring(, [:100], text-overflow: ellipsis in CSS. If the approver can't see the full command, you have the same bug. Render it all, or reject it as too long.

Day 9 - 10 Progress 🚀 Studied React: - Color Picker, Updater function, Updating Objects, Arrays and Array of Objects in State Solved 2 LeetCode Problems - 74. Search a 2d Matrix - 395. Longest Substring with atleast K repeating Char. #React #Java #DSA #LeetCode

Day 8 – #SDESheetChallenge ✅ 📚 Topic: Arrays - IV ✅ DAY - 8 Completed!! ✔️ Largest Subarray with K sum ✔️ Count subarrays with given xor K ✔️Longest Substring Without Repeating Characters @takeUforward_ #StriversSheet #DSA #Arrays #ProblemSolving #45DaysOfCode #takeUforward

Day 13 ✅ Solved: Rotate String Approach: First thought of the brute-force way by checking all possible rotations. Then used the optimized trick: if goal is a substring of s s, then the rotation is valid. Simple but elegant. 🚀 #LeetCode #DSA #Strings #Java #CodingJourney

#SDESheetChallenge @striver_79 Day 8: longest substring with unique elem solved using hash for tracking elem and shift right pointer to right of duplicate elem result in time complextiy of O(N)

DSA session done today 💪 🔹 Longest Substring Without Repeating Characters 🔹 Search in Rotated Sorted Array 🔹 Median of Two Sorted Arrays 🔹 Binary Tree Max Path Sum 🔹 Task Scheduler Median of Two Sorted Arrays was the toughest. O(log n) hurts🧠 Have you solved this one?

Master SQL SQL MASTER TREE │ ├── 1. Database Fundamentals │ ├── What is DB / DBMS / RDBMS │ ├── Tables, Rows, Columns │ ├── Primary Key │ ├── Foreign Key │ ├── Candidate Key │ ├── Composite Key │ ├── Constraints │ │ ├── NOT NULL │ │ ├── UNIQUE │ │ ├── PRIMARY KEY │ │ ├── FOREIGN KEY │ │ ├── CHECK │ │ └── DEFAULT │ └── Data Integrity │ ├── 2. SQL Data Types │ ├── Numeric │ │ ├── INT │ │ ├── BIGINT │ │ ├── DECIMAL │ │ └── FLOAT │ ├── String │ │ ├── CHAR │ │ ├── VARCHAR │ │ └── TEXT │ ├── Date & Time │ │ ├── DATE │ │ ├── TIME │ │ ├── DATETIME │ │ └── TIMESTAMP │ └── Boolean / Binary │ ├── 3. DDL (Data Definition Language) │ ├── CREATE │ │ ├── DATABASE │ │ ├── TABLE │ │ └── INDEX │ ├── ALTER │ │ ├── ADD COLUMN │ │ ├── MODIFY COLUMN │ │ └── DROP COLUMN │ ├── DROP │ │ ├── DATABASE │ │ └── TABLE │ └── TRUNCATE │ ├── 4. DML (Data Manipulation Language) │ ├── INSERT │ ├── UPDATE │ ├── DELETE │ └── MERGE / UPSERT │ ├── 5. DQL (Data Query Language) │ ├── SELECT │ ├── DISTINCT │ ├── WHERE │ │ ├── AND │ │ ├── OR │ │ └── NOT │ ├── ORDER BY │ ├── GROUP BY │ ├── HAVING │ └── LIMIT / OFFSET │ ├── 6. SQL Operators │ ├── Arithmetic ( - * /) │ ├── Comparison (= != > < >= <=) │ ├── Logical (AND OR NOT) │ ├── BETWEEN │ ├── IN │ ├── LIKE │ └── IS NULL │ ├── 7. SQL Functions │ ├── Aggregate │ │ ├── COUNT │ │ ├── SUM │ │ ├── AVG │ │ ├── MIN │ │ └── MAX │ ├── String │ │ ├── CONCAT │ │ ├── SUBSTRING │ │ ├── LENGTH │ │ └── TRIM │ ├── Numeric │ │ ├── ROUND │ │ └── ABS │ └── Date │ ├── NOW │ ├── DATEADD │ └── DATEDIFF │ ├── 8. Joins │ ├── INNER JOIN │ ├── LEFT JOIN │ ├── RIGHT JOIN │ ├── FULL JOIN │ ├── CROSS JOIN │ └── SELF JOIN │ ├── 9. Subqueries │ ├── Scalar Subquery │ ├── Correlated Subquery │ └── Nested Subquery │ ├── 10. Views │ ├── CREATE VIEW │ ├── UPDATE VIEW │ └── MATERIALIZED VIEW │ ├── 11. Indexing │ ├── Clustered Index │ ├── Non-Clustered Index │ ├── Composite Index │ └── Index Optimization │ ├── 12. Transactions │ ├── BEGIN │ ├── COMMIT │ ├── ROLLBACK │ └── SAVEPOINT │ ├── 13. ACID Properties │ ├── Atomicity │ ├── Consistency │ ├── Isolation │ └── Durability │ ├── 14. Normalization │ ├── 1NF │ ├── 2NF │ ├── 3NF │ ├── BCNF │ └── Denormalization │ ├── 15. Advanced SQL │ ├── Stored Procedures │ ├── Triggers │ ├── CTE (WITH) │ ├── Window Functions │ │ ├── ROW_NUMBER │ │ ├── RANK │ │ ├── DENSE_RANK │ │ └── PARTITION BY │ └── Recursive Queries │ ├── 16. Performance Optimization │ ├── Query Optimization │ ├── Execution Plan │ ├── Index Tuning │ └── Query Caching │ ├── 17. SQL Ecosystem │ ├── MySQL │ ├── PostgreSQL │ ├── SQLite │ ├── SQL Server │ └── Oracle DB │ └── 18. Real-World Usage ├── Backend APIs ├── Data Analytics ├── Reporting Systems ├── ETL Pipelines └── Data Warehousing

Master SQL SQL MASTER TREE │ ├── 1. Database Fundamentals │ ├── What is DB / DBMS / RDBMS │ ├── Tables, Rows, Columns │ ├── Primary Key │ ├── Foreign Key │ ├── Candidate Key │ ├── Composite Key │ ├── Constraints │ │ ├── NOT NULL │ │ ├── UNIQUE │ │ ├── PRIMARY KEY │ │ ├── FOREIGN KEY │ │ ├── CHECK │ │ └── DEFAULT │ └── Data Integrity │ ├── 2. SQL Data Types │ ├── Numeric │ │ ├── INT │ │ ├── BIGINT │ │ ├── DECIMAL │ │ └── FLOAT │ ├── String │ │ ├── CHAR │ │ ├── VARCHAR │ │ └── TEXT │ ├── Date & Time │ │ ├── DATE │ │ ├── TIME │ │ ├── DATETIME │ │ └── TIMESTAMP │ └── Boolean / Binary │ ├── 3. DDL (Data Definition Language) │ ├── CREATE │ │ ├── DATABASE │ │ ├── TABLE │ │ └── INDEX │ ├── ALTER │ │ ├── ADD COLUMN │ │ ├── MODIFY COLUMN │ │ └── DROP COLUMN │ ├── DROP │ │ ├── DATABASE │ │ └── TABLE │ └── TRUNCATE │ ├── 4. DML (Data Manipulation Language) │ ├── INSERT │ ├── UPDATE │ ├── DELETE │ └── MERGE / UPSERT │ ├── 5. DQL (Data Query Language) │ ├── SELECT │ ├── DISTINCT │ ├── WHERE │ │ ├── AND │ │ ├── OR │ │ └── NOT │ ├── ORDER BY │ ├── GROUP BY │ ├── HAVING │ └── LIMIT / OFFSET │ ├── 6. SQL Operators │ ├── Arithmetic ( - * /) │ ├── Comparison (= != > < >= <=) │ ├── Logical (AND OR NOT) │ ├── BETWEEN │ ├── IN │ ├── LIKE │ └── IS NULL │ ├── 7. SQL Functions │ ├── Aggregate │ │ ├── COUNT │ │ ├── SUM │ │ ├── AVG │ │ ├── MIN │ │ └── MAX │ ├── String │ │ ├── CONCAT │ │ ├── SUBSTRING │ │ ├── LENGTH │ │ └── TRIM │ ├── Numeric │ │ ├── ROUND │ │ └── ABS │ └── Date │ ├── NOW │ ├── DATEADD │ └── DATEDIFF │ ├── 8. Joins │ ├── INNER JOIN │ ├── LEFT JOIN │ ├── RIGHT JOIN │ ├── FULL JOIN │ ├── CROSS JOIN │ └── SELF JOIN │ ├── 9. Subqueries │ ├── Scalar Subquery │ ├── Correlated Subquery │ └── Nested Subquery │ ├── 10. Views │ ├── CREATE VIEW │ ├── UPDATE VIEW │ └── MATERIALIZED VIEW │ ├── 11. Indexing │ ├── Clustered Index │ ├── Non-Clustered Index │ ├── Composite Index │ └── Index Optimization │ ├── 12. Transactions │ ├── BEGIN │ ├── COMMIT │ ├── ROLLBACK │ └── SAVEPOINT │ ├── 13. ACID Properties │ ├── Atomicity │ ├── Consistency │ ├── Isolation │ └── Durability │ ├── 14. Normalization │ ├── 1NF │ ├── 2NF │ ├── 3NF │ ├── BCNF │ └── Denormalization │ ├── 15. Advanced SQL │ ├── Stored Procedures │ ├── Triggers │ ├── CTE (WITH) │ ├── Window Functions │ │ ├── ROW_NUMBER │ │ ├── RANK │ │ ├── DENSE_RANK │ │ └── PARTITION BY │ └── Recursive Queries │ ├── 16. Performance Optimization │ ├── Query Optimization │ ├── Execution Plan │ ├── Index Tuning │ └── Query Caching │ ├── 17. SQL Ecosystem │ ├── MySQL │ ├── PostgreSQL │ ├── SQLite │ ├── SQL Server │ └── Oracle DB │ └── 18. Real-World Usage ├── Backend APIs ├── Data Analytics ├── Reporting Systems ├── ETL Pipelines └── Data Warehousing

this is a list of 3285 substring domains and packs into 171kb of (has to be) json i need to test the trie tree to see if I can trust it to replace the blacklist.some(v => domain.includes(v));

after speeding up the api blacklist exact domain checks, i spent the day on the substring domain checks hybrid trie lookup Total time: 11255.98 ms Per domain: 11255.98 ns existing lookup Total time: 49565.00 ms Per domain: 49565.00 ns 77% faster - needs testing now

Day 428 of GFG Challenge: "Check Repeated Substring with K Replacements" Time Complexity: O(n) Space Complexity: O(1) #geekstreak60 #npci #GFGChallenge #geeksforgeeks

Day 25 of CodeSprint 3.0🚀 Solved: • Two Pointers Greedy - Maximum Area Container • Variable Size Sliding Window - Minimum Window Substring Improved two pointers, greedy optimization, sliding window & string processing💻🔥 #DSA #CPP #CodeSprint3 #TwoPointers #SlidingWindow

#Day85 of #100DaysOfCode Today's progress ✅ 🚀 Solved @geeksforgeeks POTD – Check Repeated Substring with K Replacements using sliding window approach. 🚀 Solved @LeetCode problem - Backspace String compare using two pointer. #DSA #Consistency

🗓️Day-324 of #365DaysOfCode 🎯 ✅ @geeksforgeeks #POTD: Check Repeated Substring with K Replacements ✅ @LeetCode #DCC: Number of Ways to Assign Edge Weights II #365DaysOfDSA #geeksforgeeks #gfg #leetcode #365DaysOfcoding #Java #DataStructuresAndAlgorithms #DSA

DAY 4 ✅ Check Repeated Substring with K Replacements ✅ Equal Point in Brackets 📚 Topics: Sliding Window | Prefix-Suffix Count ⚡ Consistency Builds Confidence 🚀

Day - 163 GeeksforGeeks - POTD Problem : Check Repeated Substring with K Replacements #gfg #geekstreak2026 #POTD #365daysofcode #coding #POTDwithGFG

Day 139 : Check Repeated Substring with K Replacements Approach : split string into blocks of size k and count distinct — true if 1 distinct block, or 2 distinct where one appears exactly once (replace the lone block) @geeksforgeeks #GFG