University:
American Baptist College
Course:
BU 100L | Basic Computer Science
Academic year:

2024
Views:

229

Pages:

1
Author:

Ahmat N.

Data Structures and Algorithms Basics 5.1 Introduction to Data Structures Data structures are specialized formats for organizing, processing, and storing data efficiently. This section introduces the importance of data structures in computer science, highlighting how they enable developers to manage large datasets and optimize algorithm performance. The choice of data structure can significantly impact the efficiency of an algorithm. 5.2 Common Data Structures This section covers fundamental data structures, including: • Arrays: Collections of elements stored at contiguous memory locations, providing fast access but fixed size. • Linked Lists: Composed of nodes where each node contains data and a reference to the next node, allowing dynamic memory allocation. • Stacks: A Last In First Out (LIFO) structure where elements are added and removed from the top, commonly used in function calls and undo operations. • Queues: A First In First Out (FIFO) structure where elements are added at the back and removed from the front, useful for scheduling tasks. 5.3 Introduction to Algorithms Algorithms are step-by-step procedures for solving problems. This section defines algorithms and their significance in computer science, emphasizing their role in data processing, calculation, and automation. The lecture highlights the importance of analyzing algorithms for efficiency and effectiveness. 5.4 Algorithm Complexity Understanding algorithm complexity is crucial for evaluating performance. This section introduces Big O notation, which describes the upper bound of an algorithm's time and space requirements. Common complexities, such as O(1), O(n), O(log n), and O(n^2), are explained with examples to illustrate their implications for algorithm efficiency. 5.5 Conclusion A strong foundation in data structures and algorithms is essential for effective problem-solving in computer science. Mastery of these concepts enables students to design efficient systems and applications, optimizing performance and resource utilization.