Key Concepts for Data Structure Final Exam Success
Published: 2023-07-14 04:22:07

Your data structure final exam is almost here. I remembered when I was about to take it, I wished I had a study guide to speed run through all the important concepts before I enter the testing room. Hence, in this article, we will run through the essential concepts you should remember while preparing for your data structure final exam. 

**Array-based and Linked Data Structures:**
Array-based structures, such as arrays and matrices, offer fast random access and are suitable when the size is known in advance. Linked data structures, including linked lists, doubly linked lists, and circular linked lists, utilize pointers to connect elements and provide flexibility in size. Master the implementation details, advantages, and limitations of both array-based and linked data structures.

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/bjfvw6a92p08cvo2u0oe.png)
 
You can only go back on a double linked list
When writing a function to remove a node, you need to write special cases for first and last node. Also, I often remove the node pointed by next instead of the current node, but whatever way work with you is fine.

**Stack and Queue Implementations:**
Stacks and queues are fundamental data structures with unique characteristics. Understand the Last-In-First-Out (LIFO) principle of stacks and the First-In-First-Out (FIFO) principle of queues. Familiarize yourself with stack and queue implementations using arrays, linked lists, and other variations. Pay special attention to operations like push, pop, enqueue, and dequeue, as well as the scenarios where these structures are commonly used.
If you were asked to create a stack or queue, you should use linked list, but you need to remember the way two data structure remove a node is different.
For stack (first in, last out), you need to remove the tail. Hence, we just simple mark the node second to last to point to NULL
For queue (first in, first out), you just need to push the head to the next one

**Tree Structures and Algorithms:**
Trees are hierarchical structures utilized in various applications, such as binary trees, binary search trees (BSTs), AVL trees, and B-trees. Master the concepts of tree traversal algorithms, including pre-order, in-order, and post-order traversal. Understand balanced search trees, their properties, and their applications, as well as algorithms like insertion, deletion, and searching within these structures.

**Graph Theory:**
Graphs are versatile structures used to model relationships between entities. Familiarize yourself with graph representations, including adjacency matrices and adjacency lists. Understand graph traversal algorithms like depth-first search (DFS) and breadth-first search (BFS). Learn about various graph algorithms, such as Dijkstra's algorithm for shortest paths and Kruskal's and Prim's algorithms for minimum spanning trees.
 
![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/rnr8ikynk0eydkya9q61.png)

**Sorting Algorithm:**
Data structure exams often include questions related to sorting and searching algorithms. Study commonly used sorting algorithms like bubble sort, selection sort, insertion sort, merge sort, quicksort, and heapsort. Understand their time and space complexities and their suitability for different scenarios. Similarly, explore searching algorithms like linear search, binary search, and interpolation search.
**Time and Space Complexity Analysis:**
Develop a strong understanding of time and space complexity analysis. Master the concept of Big O notation and its implications for evaluating the efficiency of algorithms. Practice analyzing the time and space complexities of various data structure operations and algorithms. Be able to differentiate between best-case, worst-case, and average-case scenarios.