What does the term “Big-O notation” describe ?

Big-O notation is a mathematical tool used in computer science to describe the performance or complexity of an algorithm. Specifically, it characterizes the upper bound of an algorithm's time complexity as the input size grows towards infinity. This means it provides a worst-case scenario for how long an algorithm will take to run, ensuring that the running time does not exceed a certain rate of growth. Option A is incorrect because Big-O describes growth rates, not exact running times which depend on hardware and specific inputs. Option B is incorrect because while space complexity can also be described using Big-O, the term itself primarily refers to time complexity in this context. Option D is incorrect because it counts specific operations rather than describing the asymptotic growth rate. Therefore, Big-O notation fundamentally defines the upper bound of an algorithm's time complexity.