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Introduction to Algorithms

An algorithm is a finite set of instructions or logic, written in order, to accomplish a certain predefined task. Algorithm is not the complete code or program, it is just the core logic(solution) of a problem, which can be expressed either as an informal high level description as **pseudo-code** or using a **flowchart**.

An algorithm is said to be efficient and fast, if it takes less time to execute and consumes less memory space. The performance of an algorithm is measured on the basis of following properties:

- Time Complexity
- Space Complexity

Time Complexity is a way to represent the amount of time needed by the program to run to completion. We will study this in details in our section.

Its the amount of memory space required by the algorithm, during the course of its execution. Space complexity must be taken seriously for multi-user systems and in situations where limited memory is available.

An algorithm generally requires space for following components:

**Instruction Space:**Its the space required to store the executable version of the program. This space is fixed, but varies depending upon the number of lines of code in the program.**Data Space:**Its the space required to store all the constants and variables value.**Environment Space:**Its the space required to store the environment information needed to resume the suspended function.

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