Data Types and Objects in Computer Science

Study Notes

Data in Computer Science

Focuses on the study of data and its manipulation through various languages.
Machines serve as storage for data, providing an interface for data operations.
Data refinement is essential, converting raw data from sources like sensors and forms into useful forms by removing outliers.

Types of Data

Atomic Data:
- Represents a single piece of information that cannot be further divided.
- Examples include a person's name or a book title.
Composite Data:
- Comprises multiple meaningful subfields, suitable for information like addresses or phone numbers.

Data Objects

A data object consists of elements, such as integers represented as a set (e.g., D = {0, ±1, ±2...}).
A student data object could include attributes like roll number, name, percentage, and address.

Data Types

Refers to classifications that determine the nature and operations of data, such as integers, floats, and characters.
Divided into two categories:
- Built-in Data Types: Directly supported by programming languages (e.g., integers, booleans, floats).
- Derived Data Types: Formed by combining built-in types and operations (e.g., lists, arrays, structures).

Abstract Data Types (ADT)

Comprises collections of data along with operations defined on that data.
Emphasizes functionality over implementation.
Examples include arrays, trees, graphs, linked lists, and matrices.

Data Structures

Defined as a set of domains, structured domains, functions, and axioms.
Types:
- Linear Data Structures: Organized sequentially (e.g., arrays, linked lists) with unique predecessors and successors.
- Non-Linear Data Structures: Organized in a manner where elements connect to multiple others, highlighting special relationships (e.g., trees, graphs).
- Static Data Structures: Fixed memory allocation (e.g., arrays).
- Dynamic Data Structures: Flexible memory size that can change during runtime (e.g., linked lists).

Algorithms

A finite, step-by-step procedure to solve a problem, independent of programming languages.
Essential criteria include:
- Input: Accepts one or more quantities.
- Output: Produces at least one quantity.
- Definiteness: Instructions must be clear.
- Finiteness: Algorithm must terminate after a certain number of steps.
- Effectiveness: Instructions should be simple enough to be performed manually.

Differences Between Program and Algorithm

A program consists of executable code written in a programming language.
An algorithm serves as an abstract solution outline for problem-solving.

Algorithm Design Tools

Pseudo Code: Informal, human-readable syntax that guides algorithm design using English-like statements.
Flowchart: Visual representation that outlines algorithm steps and their relationships, enhancing comprehension.

Example Algorithms

Finding the largest integer among a set demonstrates the basic principles behind algorithm design.
Example flowchart for printing numbers from 1 to 20 illustrates stepwise procedural logic.

Description

Explore the fundamental concepts of data, data objects, and data types in this quiz. Understand the distinctions between atomic and structured data, and how various programming languages facilitate data manipulation. Test your knowledge on data refinement processes and their applications in real-world scenarios.

Data Types and Objects in Computer Science

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Questions and Answers

What are the two types of data?

What is a data object?

A ____ data type has built-in support in a programming language.

Which of the following is NOT a built-in data type?

An abstract data type specifies how operations are implemented.

What does an abstract data type consist of?

Match the following types of data structures:

What is the purpose of an algorithm?

Which of the following criteria must all algorithms satisfy?