CS2400 M4 Flashcards
1
Q
What are algorithm constraints?
A
The time the algorithm takes to execute and the space (memory) it needs.
2
Q
Analysis of Algorithms
A
Measuring the complexity of algorithms
3
Q
Upper Bound
A
Big O notation,
T(n) = O(f(n)) if constants c > 0 and n0 >= 0 such that for all n >= n0, T(n) <= c * f(n).
4
Q
Lower Bound
A
Big Ω notation,
T(n) = Ω(f(n)) if constants c > 0 and n0 >= 0 such that for all n >= n0, T(n) >= c * f(n).
5
Q
Tight Bounds
A
Big Θ notation,
T(n) = Θ(f(n)) if constants T(n) = O(f(n)) = Ω(f(n)).
6
Q
Unbounded
A
Does not have an upper bound, lower bound, or both.
7
Q
Worst, average, and best case
A
Measuring execution time depending on the nature of data itself, NOT sample size.
