Most coding interview questions don’t test how many problems you’ve memorized. They test whether you recognize the pattern hiding in plain sight. Once that clicks, interviews stop feeling like chaos and start feeling… familiar. Here are the most common DSA patterns every interview-ready developer should have on speed dial: 1. Hashing (HashMap / HashSet) When things get hard… throw a HashMap at it.Use it for: - Fast lookups - Counting frequencies - Tracking visited elements - Turning O(n²) pain into O(n) peace 2. Two Pointers Two indices, one elegant solution. Perfect for: - Sorted arrays - Pair problems - Reversals and partitions 3. Sliding Window For anything involving subarrays or substrings Best when: - You need max/min/length - The window grows and shrinks intelligently 4. Binary Search Not just for “find X in sorted array”. Use it when: - The answer space is sorted - You’re minimizing or maximizing something - You hear the words “minimum possible” or “maximum feasible” 5. Stack When order matters and you need to go back. Think: - Valid parentheses - Next greater/smaller element - Undo operations 6. BFS / DFSF or trees, graphs, and grids. Choose: - BFS for shortest paths - DFS for depth, paths, and exploration The real unlock? 👉 Interview questions repeat. Patterns repeat harder. Once you train your brain to spot patterns first,coding becomes execution, not panic. Practice problems, yes. But master the patterns: that’s how you walk into interviews calm, clear, and dangerous (in a good way).

Most candidates solve interview problems. Strong candidates show how they think. The real upgrade in interviews is moving from guessing to a structured problem-solving process. Not because interviewers want steps, but because they want clarity. A solid framework helps you: - Think clearly under pressure - Avoid getting stuck - Catch edge cases and optimizations - Sound calm, professional, and experienced The goal: make the process automatic. The 3-Phase Interview Framework 1. Understand Clarify requirements, constraints, and edge cases before coding. 2. Design Start brute force, analyze time & space, then optimize using patterns(Binary Search, HashMaps, Sliding Window, Two Pointers, Heaps), this is for dsa oriented interviews. 3. Implement Walk through examples, write clean code, test edge cases, discuss trade-offs. This mindset separates candidates who eventually get there from those who look interview-ready from minute one. Don’t just practice problems. Practice the process. But remember you need to sound human, not a robot. So no cramming just mastering the art. Lemme know what y'all think

in my experience, comparing BigDecimal using ".equals()" does not correctly compare numbers. when comparing "1000" and "1000.00" both BigDecimal data types, java considers these 2 values to be different. I have found that using the "compareTo()" method to yield better results. you may save a value in json body as "1000", but when you retrieve the values again, it is saved as "1000.00" then when you for instance want to update an entity, if you use .equals(), java will consider these 2 values to be different. this is my code snippet for instance. if (updateRequest.price() != null && updateRequest.price().compareTo(p.getPrice()) != 0 ){ p.setPrice(updateRequest.price()); changes = true; }

A family member was having a seizure during the meeting. I will see you soon...

Hi everyone, Hope you're having a productive week. I'm currently following the Spring Boot for Beginners course and running into a persistent issue while trying to integrate Spring AI (OpenAI starter). My project is using the Spring Boot 4.0.0 parent POM. When I add the required dependency (spring-ai-openai-spring-boot-starter), I get the following error during my Maven build: Dependency 'org.springframework.ai:spring-ai-openai-spring-boot-starter:' not found I've checked the official documentation, which states: "Spring AI supports Spring Boot 3.4.x and 3.5.x." My Questions to the Community are : 1. Has anyone successfully managed to integrate Spring AI into a project using the Spring Boot 4.0.0 ? If so, what specific Spring AI BOM version did you use, and did you need any custom repository configuration? 2. Since Spring AI officially only supports the 3.x line, is the general consensus that I should downgrade my project's parent POM to Spring Boot 3.5.0 to ensure dependency resolution and stability? Any advice or confirmation from someone who has navigated this version conflict would be greatly appreciated 🙏 Thank you