CST 370 - Week 6

 Hey everyone,

This week, I explored several fundamental data structures and algorithms that are essential for efficient data organization and manipulation. I started with AVL Trees, where I learned how self-balancing binary search trees maintain their height through rotations. From the lecture and exercises, I practiced identifying whether a tree is AVL and performed left and right rotations to restore balance. The AVL tree visualization tool was especially helpful in understanding how the tree structure changes dynamically during insertions.

Additionally, I shared about my experience in comparing test cases in our homework assignments with my classmates on Discord. I shared how to add the "a.out" file and use the manual commands provided by the professor.

I also studied 2-3 Trees, a type of balanced search tree where nodes can contain two or three children. I learned how values are inserted and how nodes split when they become overfull. The video introduction and exercises clarified how this structure guarantees logarithmic height, helping maintain search efficiency.

Moving forward, I learned about Heaps and the Heapsort algorithm. I now understand how a Max Heap maintains the largest element at the root. I also learned about constructing heaps using both array-based methods and the bottom-up approach. 

Finally, I studied Hashing, an efficient technique for data retrieval. I explored how hash functions work, the problem of collisions, and strategies like chaining and open addressing to handle them. I also learned about load factors and the importance of rehashing when a hash table becomes too full.

This week’s readings, videos, and exercises gave me a comprehensive understanding of these advanced data structures and algorithms, and how they contribute to optimizing performance in various computing tasks.

Comments

Post a Comment

Popular posts from this blog

CST 370 - Week 1

 Hey everyone, This week, we learned several important topics that form the foundation of computer science and programming. We started with GitHub and practiced using manual commands like git init, git add, git commit, and git push to manage our code. This helped us understand version control and how to keep track of changes when working on projects, especially when collaborating with others. We were also introduced to algorithms and learned what they are—step-by-step methods for solving problems. One example we focused on was Euclid’s Algorithm for finding the greatest common divisor (GCD) of two numbers. It uses a simple but powerful idea: repeatedly replace the numbers with GCD(b, a % b) until the second number becomes zero. We also practiced writing pseudocode, which helped us plan out algorithms in plain language before coding. We also had a homework assignment to help us further understand GitHub commands. Later in the week, we learned about graphs, both weighted and unweight...
Read more

CST 370 - Week 5

 Hey everyone! This week, I explored several important algorithm design techniques and deepened my understanding of how they are applied in solving complex problems efficiently. One of the key highlights was learning about Quick Sort , a widely used sorting algorithm that relies on the Divide-and-Conquer strategy. I now understand how Quick Sort works by dividing the array into smaller parts around a pivot, sorting those parts recursively, and then combining the results. I also learned about its efficiency and how its performance depends on the choice of the pivot. I also studied Binary Tree traversal methods, such as inorder, preorder, and postorder, and how each serves a specific purpose when working with hierarchical data. Alongside traversal, I learned how to calculate the height of a binary tree , which is a foundational concept for evaluating the balance and efficiency of tree-based data structures. I even added my insights on the class Discord group, explaining an easy calc...
Read more

CST 370 - Week 4

 Hey everyone! This week in class, I focused on two main things: learning about Merge Sort and reviewing for the upcoming midterm . We covered Merge Sort in detail, and it really helped me understand how divide-and-conquer algorithms work. I learned that Merge Sort breaks down an array into smaller parts, sorts each part, and then merges them back together in a sorted order. What stood out to me is how efficient it is, especially for large datasets, with a time complexity of O(n log n) . I found the recursive nature of the algorithm interesting, and practicing it helped me see how smaller problems can be solved independently and then combined to solve the larger problem. Aside from learning new material, a big part of this week was focused on reviewing for the midterm . I went over topics from previous weeks like brute-force algorithms, string matching, and graph traversal methods (DFS and BFS). I also spent time practicing problems and using flashcards to reinforce key concepts....
Read more