R4.1 The characteristics and applications of algorithms in digital analysis:

Algorithms 

In the world of IT, an algorithm is a set of well-defined instructions that a computer can follow to solve a specific problem or perform a particular task, support calculations or to deal with problem solving. Algorithms have several characteristics;

• finiteness - finite number of steps, this means that the algorithm will continue to cycle until a value is true (1), this means it should in have a point where the algorithm stops if a result has not been achieved as it could loop and never end as it will not solve the problem or complete the cycle.

• unambiguous - steps must be clear and lead to one meaning, as the logic applied to the algorithm should provide a purposeful sequence of process that will be clear.

• clearly defined inputs and outputs - A good algorithm has a specific step-by-step process that defines the inputs to the system, such as an on (1) or off (0) and this should be consistently applied and understood by the system.

• logical sequencing of steps - Most applications, programs and systems follow a logical order. One of the first logical sequences done by a computer system is the POST process, or, Power On Self Test. This process ensures that the system starts up correctly by checking that certian parameters are true (1) and if not (0) then a message is presented to the user.

• iteration - repetition of steps until results achieved, oftern refered to as a cycle, the iteration is where the algorithm will loop until a statement or variable is met, or true (1)

• selection - input leading to choice of step

• structured English - The creation of an algorthm can be done using "Structured English" this is a language between the normal written english language and computer programming languages. It is intended to allow those without any programming knowledge or understanding to be able to follow instructions that would enable them to understand the operation of a system or algorthm.

Applications of algorithms for digital analysis:

• automate calculations to improve efficiency of a process

• design a step by step solution to solve a problem

• supports machine learning for data analysis

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R4.2 The process of computational thinking and tools applied in problem solving and algorithm design.

Process of computational thinking:

• decomposition - breaking down a complex problem or system into manageable components

• pattern recognition - identification of patterns within problems

• abstraction - analyse information, filter and remove unnecessary detail

• action:

o sequence - order of processes

o selection - execution only when conditions met

o iteration - repetition until conditions met

Tools for problem solving and algorithm design:

• decomposition diagram

• flowchart

• pseudo code

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