Western Governors University (WGU) ICSC2100 C949 Data Structures and Algorithms I Practice Exam

Big-O notation is primarily used to describe the upper bound of an algorithm's running time or space requirements, and it is most effectively applied in worst-case scenarios. This is because the worst case provides a guarantee on the maximum amount of time or space an algorithm will require, regardless of the input.

By focusing on the worst-case scenario, you can ensure that the algorithm will perform efficiently under all circumstances, which is crucial for understanding performance limitations. This approach gives developers and analysts a conservative estimate of how algorithms will behave when pushed to their limits, allowing them to make informed decisions when selecting algorithms for various applications.

Best case and average case scenarios provide useful insights into performance but do not offer the same level of assurance about the algorithm's efficiency in all situations. Real-world scenarios are important for practical applications, but they can vary widely and are influenced by many factors, making them less reliable for theoretical analysis compared to the worst-case perspective.