Characteristics and Applications of algorithms in digital analysis

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Characteristics and Applications of algorithms in digital analysis

Algorithms - An algorithm is a plan, or well-defined set of step by step instructions, to solve a problem.

Characteristics

Finiteness - The algorithm should solve the problem in a given number of steps, it cannot be looping.

Unambiguous - The steps in the algorithm must be clear and precise with the steps clearly defined

Iteration - The algorithm should use discrete steps. That means each step is carried out based on the previous step.

Selection - Any input into the algorithm should lead to a specified step(s).

Feasibility - The algorithm should be able to be implemented with the specified and defined resources. This means that the algorithm should provide feasible solution to the problem.

Structured English - Algorithms can be written in structured English. Structured English allows users with no programming knowledge to understand the algorithm.

Independent - An algorithm should have step-by-step directions, which should be independent of any programming code.

Inputs and Outputs - The inputs and outputs produced by an algorithm should be clearly defined. Each algorithm should have 0 or more inputs and at least 1 output.

Logical sequencing of steps - The steps in the algorithm should follow a logical sequence to solve the problem. This means that the steps should flow on step by step with no 'jumping'.





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