What does Big O notation help to describe?

Big O notation is a mathematical concept used to describe the performance characteristics of algorithms, specifically in terms of their time and space complexity. It provides a high-level understanding of how an algorithm's running time or memory consumption grows relative to the size of the input data. This allows developers and computer scientists to compare the efficiency of algorithms and make informed decisions about which one to use based on resource constraints.

By focusing on the worst-case scenario in terms of efficiency, Big O notation allows for a simplified representation that captures the essence of how the algorithm will perform as the input size increases. This abstraction is crucial when designing algorithms, as it helps to predict scalability and potential performance bottlenecks.

Understanding the time or space complexity through Big O notation is fundamental in algorithm analysis, as it guides engineers in optimizing their code and choosing the appropriate algorithms for specific tasks, enabling efficient solution development in computer science.