cs chapter 4

Computational thinking

The thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by a computer

Decomposition

Breaking a problem into smaller, more manageable parts which are then easier to solve

Usually first step in the problem solving process

One of the skills required for computational thinking

Why is decomposition beneficial?

Sub-problems can be worked on by different teams at the same time

As smaller algorithms are developed for each sub-problem, it is easier to spot and correct errors

Code can also be reused when the algorithm is developed into a program

Abstraction

The process of removing or hiding unnecessary detail so that only the important points remain

One of the skills required for computational thinking

Higher the level of abstraction, lesser detail is included

Why is abstraction important?

It is important as when we create algorithms, we abstract the basic details of the problem so that we represent them in a way that the compute is able to process

High level programming languages are also at a high level of abstraction (very far removed from the actual language of a computer of a stream of 0s and 1s) to make it easier for a programmer to understand and write code

Sub-program

A self contained module of code that performs a specific task. It can be called by the main program when it is needed

What needs to be identified when designing a solution to a problem?

Inputs, outputs, initialization and processing requirements should be identified at the outset