Save
A-level Computer Science
School Notes
Big O
Save
Share
Learn
Content
Leaderboard
Share
Learn
Created by
Ana Saker
Visit profile
Cards (40)
What does Big O Notation measure?
Steps
and
memory
usage
change
with
data
View source
How does a linear algorithm grow?
It
grows
in
proportion
to the
amount
of
data
View source
What characterizes an exponential growth rate?
Rate
increases
at the
rate
of
k
n
k^n
k
n
View source
What does constant time complexity mean?
Time
does
not
change
with
more
elements
View source
How does polynomial time complexity behave?
Time increases
as
a
polynomial
function
of
elements
View source
What does logarithmic time complexity indicate?
Time
increases
at a
rate
of
log
k
n
\log_k n
lo
g
k
n
View source
What
are the types of Big O Notation complexities?
Constant
O(1)
Logarithmic
O(log
n
)
Linear
O
(
n
)
Polynomial
O(n^
k
)
Exponential
O(k^n)
View source
How does logarithmic time complexity compare to linear?
It increases more slowly than linear time
View source
How does linear time complexity behave when elements double?
Time needed also doubles
View source
What does polynomial time complexity indicate when elements double?
Time increases by a factor of
k
k
k
View source
How does exponential time complexity behave?
Time increases rapidly as elements increase
View source
How does memory usage relate to Big O Notation?
Memory
usage
can
also
be
evaluated
with
Big
O
View source
How can Big O Notation be used in algorithm comparison?
Evaluates
performance
of algorithms
Compares time and memory usage
Provides impression of performance variation with data
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
1
1
1
?
1
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
2
2
2
?
2
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
3
3
3
?
2.58
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
4
4
4
?
3
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
5
5
5
?
3.32
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
6
6
6
?
3.58
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
7
7
7
?
3.8
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
8
8
8
?
4
View source
What is the time for
log
2
n
\log_2 n
lo
g
2
n
when
n
=
n =
n
=
9
9
9
?
4.16
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
1
1
1
?
2
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
2
2
2
?
4
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
3
3
3
?
9
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
4
4
4
?
16
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
5
5
5
?
25
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
6
6
6
?
36
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
7
7
7
?
49
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
8
8
8
?
64
View source
What is the time for
n
2
n^2
n
2
when
n
=
n =
n
=
9
9
9
?
81
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
1
1
1
?
2
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
2
2
2
?
4
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
3
3
3
?
8
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
4
4
4
?
16
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
5
5
5
?
32
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
6
6
6
?
64
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
7
7
7
?
128
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
8
8
8
?
256
View source
What is the time for
2
n
2^n
2
n
when
n
=
n =
n
=
9
9
9
?
512
View source