Algorithm Analysis Data
Structures and Sorting Big
O Notation and Operations
Test Bank
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Terms in this set (28)
Why is theoretical analysis important in algorithm It helps understand how runtime grows as input size N increases,
design? regardless of hardware speed.
What is the Big-O notation for constant time O(1) - indicates that the operation takes the same amount of time
operations? regardless of input size.
What does O(N) represent in Big-O notation? Linear time complexity, where doubling the input size doubles the time
taken.
What is the Big-O notation for quadratic time O(N²) - where doubling the input size quadruples the time taken.
complexity?
What is the factorial time complexity notation? O(N!) - represents a complexity that becomes impractical for large N.
What are the four fundamental operations Access, Insert, Delete, Search.
analyzed in data structures?
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