Which statement describes Big-O worst-case growth?

• A. Best-case growth
• B. Average-case growth
• C. Describes worst-case growth
• D. Describes memory usage

Answer: (C)

Big-O worst-case growth describes how the running time (or resources) of an algorithm increases in the most demanding input scenario as the input size grows. It provides an upper bound that holds for all inputs beyond a certain size, focusing on the worst possible case. This is why the statement describing worst-case growth is the best fit: it guarantees how bad the performance can be, regardless of the specific inputs, by ignoring constants and lower-order terms and looking at the dominant growth rate. Best-case growth talks about the fastest possible inputs, which isn’t what worst-case analysis measures; average-case depends on how likely different inputs are, and memory usage (space) is a related but separate dimension.