CSCI 3212 Midterm Exam

Midterm Exam, 03/05/2024, in person during lab

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1. Midterm Preparation Guide

  • Introduction:

Welcome to the midterm preparation guide for your algorithm course! This guide aims to help you prepare effectively for the upcoming midterm exam. The exam will assess your understanding of Binary Search Trees (BST), Hash Tables, Breadth-first Search (BFS), and Depth-first Search (DFS), including their time and space complexities, and comparative performance.

1.1. Key Topics to Study:

  • Binary Search Trees (BST):

    1. Understand the structure and operations of BST, including insertion, deletion, and searching.

    2. Analyze the time and space complexities of BST operations.

    3. Consider scenarios where BSTs are suitable and understand their advantages and limitations compared to other data structures.

  • Hash Table:

    1. Grasp the concept of hashing and collision resolution techniques used in hash tables.

    2. Implement basic hash table operations such as insertion, deletion, and searching.

    3. Evaluate the time complexity of hash table operations and understand factors influencing their performance.

  • Breadth-first Search (BFS) and Depth-first Search (DFS):

    1. Understand the algorithms for BFS and DFS traversal of graphs.

    2. Implement BFS and DFS algorithms for graph traversal and understand their applications.

    3. Analyze the time and space complexities of BFS and DFS algorithms.

  • Performance Comparison

    1. Compare the performance of different algorithms and data structures for solving common problems.

    2. Understand the factors influencing algorithm performance, such as input size and data distribution.

    3. Analyze trade-offs between time complexity, space complexity, and practical performance considerations.

1.2. Study Tips

  • Pseudocode and Diagrams: Practice writing pseudocode for each algorithm and draw diagrams to visualize the process.

  • Implement the Algorithms: Write your own code implementations for each algorithm to reinforce your understanding.

  • Solve Practice Problems: Engage with practice problems that require you to choose the most appropriate algorithm based on a set of requirements.

  • Group Study: Collaborate with peers to discuss and solve complex problems, which can enhance your understanding of the material.

  • Utilize Online Resources: Explore online simulations and visualizations of algorithms to see them in action.

1.3. Resources

  • Textbooks: Refer to standard algorithms textbooks on the course index page.

  • Online Courses: Platforms like Coursera, edX, and Khan Academy offer courses on algorithms.

  • Visualization Tools: Websites like VisuAlgo and Algorithm-visualizer provide interactive visualizations of algorithms, helping you to better understand their mechanics.

1.4. Practice Quiz

  • Before the actual quiz, attempt a practice quiz that includes a mix of multiple-choice questions, short answer questions, and coding problems. This will help you gauge your preparedness and identify areas that need further review.