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Harsh Mishra
Harsh Mishra

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Queue, DSA Complete Syllabus

Course Curriculum: Mastering Queue Data Structure and Algorithms

This course covers all aspects of queues, from the basics to advanced concepts and applications. By the end of this course, learners will have a deep understanding of queues and their variations, enabling them to solve problems efficiently in academic, professional, and competitive programming contexts.


Module 1: Introduction to Queues

  1. Understanding Data Structures
    • Overview of Linear and Non-linear Data Structures.
    • Real-life examples and use cases.
  2. What is a Queue?
    • Definition and concept of First-In-First-Out (FIFO).
    • Characteristics of queues.
  3. Real-world Applications of Queues
    • Customer service systems.
    • Scheduling and task management.
    • Data buffering and streaming.
  4. Comparison with Other Data Structures
    • Queue vs Stack.
    • Queue vs Deque.
    • Queue vs Linked List.
  5. Environment Setup
    • Tools and programming environments for practicing queues.

Module 2: Implementing Queues

  1. Queue Operations
    • Enqueue (Insertion), Dequeue (Removal).
    • Peek/Front and Rear/Back.
    • IsEmpty and Size operations.
  2. Queue Implementation Using Arrays
    • Fixed-size queue.
    • Dynamic resizing techniques.
  3. Queue Implementation Using Linked List
    • Node structure.
    • Efficient memory utilization.
  4. Circular Queue
    • Concept and advantages.
    • Implementation using arrays and linked lists.
  5. Comparison of Implementations
    • Time and space complexity analysis.
    • Trade-offs of different implementations.

Module 3: Variants of Queues

  1. Double-ended Queue (Deque)
    • Definition and operations (insert/delete at both ends).
    • Applications in sliding window problems.
  2. Priority Queue
    • Introduction to priority-based operations.
    • Implementation using arrays, linked lists, and heaps.
  3. Circular Queue
    • Efficient utilization of array space.
    • Applications in buffer management.
  4. Multiple Queues in a Single Array
    • Design and implementation.
    • Use cases in multi-threaded environments.

Module 4: Applications of Queues

  1. Queue in Scheduling Problems
    • CPU scheduling (FCFS).
    • Round-robin scheduling.
  2. Queue in Data Streaming
    • Real-time buffering systems.
    • Rate-limiting and throttling.
  3. Breadth-First Search (BFS)
    • Graph traversal using queues.
    • Applications in shortest path algorithms.
  4. Caching Systems
    • Least Recently Used (LRU) Cache implementation.
    • Optimal cache replacement strategies.
  5. Binary Tree Operations
    • Level-order traversal.
    • Serialization and deserialization.

Module 5: Advanced Queue Concepts

  1. Monotonic Queues
    • Definition and applications.
    • Solving optimization problems (e.g., sliding window maximum).
  2. Implementation of Priority Queues
    • Binary heaps and their role in priority queues.
    • Operations: Insert, ExtractMin/ExtractMax.
  3. Double-ended Priority Queue
    • Efficient implementation.
    • Real-world use cases.
  4. Task Scheduling with Dependencies
    • Topological sorting using Kahn's algorithm.
    • Role of queues in dependency resolution.

Module 6: Optimized Techniques and Complex Problems

  1. Handling Large Data with Queues
    • Distributed queuing systems (e.g., Kafka, RabbitMQ).
    • Message queuing protocols.
  2. Queue in Parallel Processing
    • Job queues in multiprocessing.
    • Thread-safe queues.
  3. Optimizing Queue Performance
    • Dynamic resizing.
    • Amortized analysis of operations.

Module 7: Practical Projects and Case Studies

  1. Simulation of a Customer Service System
    • Multi-server queue simulation.
  2. Queue-based Traffic Management System
    • Simulating real-world traffic flow using queues.
  3. Data Streaming Application
    • Designing a message queue for live data streaming.
  4. Cache Management System
    • Implementing an LRU Cache using Deques and Priority Queues.

Module 8: Competitive Programming with Queues

  1. Common Queue Problems in Competitions
    • Problems from platforms like Codeforces, LeetCode, and HackerRank.
  2. Problem-Solving Techniques
    • Identifying queue-based solutions.
    • Debugging common errors.
  3. Time Optimization
    • Reducing overhead in queue operations.
    • Space-efficient implementations.

Module 9: Queue Applications in Real-world Systems

  1. Event-driven Programming
    • Queues in event-loop systems.
    • Application in Node.js and other frameworks.
  2. Operating Systems
    • Role of queues in process management.
    • Disk scheduling algorithms (e.g., SCAN, C-SCAN).
  3. Database Management
    • Queues in transaction handling.
    • FIFO semantics in log management.
  4. Machine Learning and AI
    • Using queues in parallel processing tasks.

Module 10: Final Assessment and Mastery

  1. Comprehensive Coding Projects
    • Building a multi-level priority queue system.
    • Implementing a task scheduler with dependencies.
  2. Capstone Project
    • Design and implementation of a real-world application heavily reliant on queues.
  3. Final Examination
    • Theory and practical coding exam to assess mastery.
  4. Feedback and Next Steps
    • Personalized feedback for improvement.
    • Recommendations for further study and advanced topics.

This curriculum ensures a complete understanding of queues and their applications, from foundational concepts to advanced real-world implementations.

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