BASIC DIFFERENCES BETWEEN SPACE COMPLEXITY AND TIME COMPLEXITY
SPACE COMPLEXITY:
The space complexity of an algorithm is the amount of memory it requires to run to completion.
the space needed by a program contains the following components:
1) Instruction space:
-stores the executable version of programs and is generally fixed.
2) Data space:
It contains:
a) Space required by constants and simple variables.Its space is fixed.
b) Space needed by fixed size stucture variables such as array and structures.
c) dynamically allocated space.This space is usually variable.
3) enviorntal stack:
-Needed to stores information required to reinvoke suspended processes or functions.
the following data is saved on the stack
- return address.
-value of all local variables
-value of all formal parameters in the function..
TIME COMPLEXITY:
The time complexity of an algorithm is the amount of time it needs to run to completion. namely space
To measure the time complexity we can count all operations performed in an algorithm and if we know the time taken for each operation then we can easily compute the total time taken by the algorithm.This time varies from system to system.
Our intention is to estimate execution time of an algorithm irrespective of the computer on which it will be used. Hence identify the key operation and count such operation performed till the program completes its execution.
The time complexity can be expressd as a function of a key operation performed.
The space and time complexity is usually expressed in the form of function f(n),where n is the input size for a given instance of a problem being solved.
f(n) helps us to predict the rate of growthof complexity that will increase as size of input to the problem increases.
f(1) also helps us to predict complexity of two or more algorithms in order ro find which is more efficient.
Polynomial vs non polynomial time complexity
time complexity is 2^57..and space complexity is 2^(n+1).
"Running Time" is essentially a synonym of "Time Complexity", although the latter is the more technical term. "Running Time" is confusing, since it sounds like it could mean "the time something takes to run", whereas Time Complexity unambiguously refers to the relationship between the time and the size of the input.
The algorithm will have both a constant time complexity and a constant space complexity: O(1)
Time complexity and space complexity.
5 hours
5 hours
Time complexity and space complexity.
according to Einstein----nothing
The complexity of an algorithm is the function which gives the running time and/or space in terms of the input size.
contiguous is "separated in space" and continuous is "separated in time"
you can find an example in this link ww.computing.dcu.ie/~away/CA313/space.pdfgood luck