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 pseudocode or using a flowchart.

Every Algorithm must satisfy the following properties:

  1. Input– There should be 0 or more inputs supplied externally to the algorithm.
  2. Output– There should be atleast 1 output obtained.
  3. Definiteness– Every step of the algorithm should be clear and well defined.
  4. Finiteness– The algorithm should have finite number of steps.
  5. Correctness– Every step of the algorithm must generate a correct output.

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 :

  1. Time Complexity
  2. Space Complexity

Space Complexity

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(including temporary variables) value.
  • Environment Space: Its the space required to store the environment information needed to resume the suspended function.

Time Complexity

Time Complexity is a way to represent the amount of time required by the program to run till its completion. It’s generally a good practice to try to keep the time required minimum, so that our algorithm completes it’s execution in the minimum time possible.

For any query or issue, feel free to discuss on