🧩 Core Computer Science Concepts

🧠 Big-O Notation
🗂️ Data Structures
🔁 Recursion
🧵 Concurrency vs Parallelism
📦 Memory Management
🔒 Race Conditions
🌐 Networking Basics
⚙️ Operating Systems
🧪 Testing Strategies
📐 System Design

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Create, Read, Update, Delete – the core operations of most web apps.

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Publishing your app to a live server or cloud platform.

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Store sensitive data like API keys securely outside your codebase.

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Tools that simplify development (e.g., React, Express, Django).

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Foundation of data communication on the web.

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Connecting different systems or services (e.g., payment gateways, APIs).

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Compact way to securely transmit information between parties for authentication.

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Tool for automating deployment and scaling of containerized applications.

L – Load Balancer
Distributes incoming traffic across multiple servers for better performance.

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Functions that run during request/response cycles in backend frameworks.

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Tool to manage JavaScript packages and dependencies.

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Maps database tables to objects in code (e.g., Sequelize, Prisma).

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Powerful open-source relational database system.

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Used for handling background tasks (e.g., RabbitMQ, Redis queues).

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Architectural style for designing networked applications using HTTP.

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Store user data across multiple requests (e.g., login sessions).

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U – UX (User Experience)
Designing intuitive and enjoyable user interactions.

V – Version Control
Track and manage code changes (e.g., Git, GitHub).

W – WebSockets
Enable real-time communication between client and server.

X – XSS (Cross-Site Scripting)
Security vulnerability where attackers inject malicious noscripts into web pages.

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The Snakes Game project is a classic implementation of the popular game
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The Cash Flow Minimizer project involves solving a cash flow optimization problem using graphs, multisets, and heaps. Given a set of transactions among a group of people, the objective is to minimize the total number of transactions required to settle all debts

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✅ Top 50 DSA (Data Structures & Algorithms) Interview Questions 📚⚙️

1. What is a Data Structure?
2. What are the different types of data structures?
3. What is the difference between Array and Linked List?
4. How does a Stack work?
5. What is a Queue? Difference between Queue and Deque?
6. What is a Priority Queue?
7. What is a Hash Table and how does it work?
8. What is the difference between HashMap and HashSet?
9. What are Trees? Explain Binary Tree.
10. What is a Binary Search Tree (BST)?
11. What is the difference between BFS and DFS?
12. What is a Heap?
13. What is a Trie?
14. What is a Graph?
15. Difference between Directed and Undirected Graph?
16. What is the time complexity of common operations in arrays and linked lists?
17. What is recursion?
18. What are base case and recursive case?
19. What is dynamic programming?
20. Difference between Memoization and Tabulation?
21. What is the Sliding Window technique?
22. Explain Two-Pointer technique.
23. What is the Binary Search algorithm?
24. What is the Merge Sort algorithm?
25. What is the Quick Sort algorithm?
26. Difference between Merge Sort and Quick Sort?
27. What is Insertion Sort and how does it work?
28. What is Selection Sort?
29. What is Bubble Sort and its drawbacks?
30. What is the time and space complexity of sorting algorithms?
31. What is Backtracking?
32. Explain the N-Queens Problem.
33. What is the Kadane's Algorithm?
34. What is Floyd’s Cycle Detection Algorithm?
35. What is the Union-Find (Disjoint Set) algorithm?
36. What are topological sorting and its uses?
37. What is Dijkstra's Algorithm?
38. What is Bellman-Ford Algorithm?
39. What is Kruskal’s Algorithm?
40. What is Prim’s Algorithm?
41. What is Longest Common Subsequence (LCS)?
42. What is Longest Increasing Subsequence (LIS)?
43. What is a Palindrome Substring problem?
44. What is the difference between greedy and dynamic programming?
45. What is Big-O notation?
46. What is the difference between time and space complexity?
47. How to find the time complexity of a recursive function?
48. What are amortized time complexities?
49. What is tail recursion?
50. How do you approach solving a coding problem in interviews?

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