Data Management Concepts and User-Defined Data Types in C++ | Study notes Data Structures and Algorithms

Data Management concepts:

In C++, data management concepts are crucial for handling data efficiently and

securely within data structures. Below are some key data management concepts

applied to data structures in C++:

1. **Encapsulation:** Encapsulation is a fundamental concept in C++ that enables

data hiding and ensures that the internal implementation details of data structures are

hidden from external users.

2. **Data Abstraction:** Data abstraction in C++ involves defining the interface of a

data structure independently of its implementation. This simplifies the usage of data

structures and promotes code reusability.

3. **Constructors and Destructors:** Constructors are special member functions in

C++ classes that are responsible for initializing objects of the data structure. They set

default values and allocate resources as needed. Destructors, on the other hand, are

used to release resources and clean up memory when an object goes out of scope or is

explicitly delete.

5. **Memory Management:** C++ allows manual memory management using

dynamic memory allocation (e.g., `new` and `delete`) for data structures that require

memory to be allocated at runtime.

6. **Operator Overloading:** Operator overloading in C++ allows you to define

custom behavior for operators like `+`, `-`, `*`, etc.

8. **Data Validation:** Proper data validation is essential in data structures to ensure

that the data being stored is valid and consistent.

9. **Exception Handling:** Exception handling is crucial for robust data

management

By incorporating these data management concepts in data structure design and

implementation, you can create efficient, secure, and maintainable C++ programs that

handle data effectively.

Data types –

primitive and non-primitive:-

Primitive and non-primitive data structures are two broad categories that classify the

types of data structures used in computer programming and data management. Here's

a brief explanation of each:

**Primitive Data Structure:**

Primitive data structures are basic or fundamental data types directly supported by the

programming language. They are simple and represent the building blocks of more

complex data structures. Common examples of primitive data structures include:

- Integer (int): Represents whole numbers.

- Floating-Point (float/double): Represents numbers with decimal points.

- Character (char): Represents a single character.

- Boolean (bool): Represents true or false values.

Partial preview of the text

Download Data Management Concepts and User-Defined Data Types in C++ and more Study notes Data Structures and Algorithms in PDF only on Docsity!

 Data Management concepts: In C++, data management concepts are crucial for handling data efficiently and securely within data structures. Below are some key data management concepts applied to data structures in C++:

Encapsulation: Encapsulation is a fundamental concept in C++ that enables data hiding and ensures that the internal implementation details of data structures are hidden from external users.
Data Abstraction: Data abstraction in C++ involves defining the interface of a data structure independently of its implementation. This simplifies the usage of data structures and promotes code reusability.
Constructors and Destructors: Constructors are special member functions in C++ classes that are responsible for initializing objects of the data structure. They set default values and allocate resources as needed. Destructors, on the other hand, are used to release resources and clean up memory when an object goes out of scope or is explicitly delete.
Memory Management: C++ allows manual memory management using dynamic memory allocation (e.g., new and delete) for data structures that require memory to be allocated at runtime.
Operator Overloading: Operator overloading in C++ allows you to define custom behavior for operators like +, -, *, etc.
Data Validation: Proper data validation is essential in data structures to ensure that the data being stored is valid and consistent.
Exception Handling: Exception handling is crucial for robust data management By incorporating these data management concepts in data structure design and implementation, you can create efficient, secure, and maintainable C++ programs that handle data effectively. Data types – primitive and non-primitive:- Primitive and non-primitive data structures are two broad categories that classify the types of data structures used in computer programming and data management. Here's a brief explanation of each: Primitive Data Structure: Primitive data structures are basic or fundamental data types directly supported by the programming language. They are simple and represent the building blocks of more complex data structures. Common examples of primitive data structures include:
- Integer (int): Represents whole numbers.
- Floating-Point (float/double): Represents numbers with decimal points.
- Character (char): Represents a single character.
- Boolean (bool): Represents true or false values.

These data types are usually used to store individual pieces of data and have a direct mapping to hardware-level data representations.

Non-Primitive Data Structure: Non-primitive data structures are more complex and can hold a collection of data elements. Unlike primitive data types, non-primitive data structures are composed of one or more primitive or non-primitive data types. Common examples of non- primitive data structures include:
- Arrays: A collection of elements of the same data type, accessed using an index.
- Linked Lists: A linear data structure where elements are stored in nodes, each containing a value and a reference to the next node.
- Stacks: Follows the Last In, First Out (LIFO) principle, commonly used in function calls and expression evaluation.
- Queues: Follows the First In, First Out (FIFO) principle, used for managing tasks in a sequential order.
- Trees: A hierarchical data structure with a root node and child nodes organized in a branching pattern.
- Graphs: A set of nodes connected by edges, used to model complex relationships. Non-primitive data structures are designed to solve specific data organization and management problems, and they often require more memory and operations for their implementation compared to primitive data types. In summary, primitive data structures represent individual data elements, while non- primitive data structures organize and manage collections of data, allowing for more sophisticated data management and manipulation.  Types of Data Structures- Linear &Non Linear Data Structures: Data structures can be categorized into two main types: linear data structures and non- linear data structures. Let's explore each type:
Linear Data Structures: Linear data structures are those in which the data elements are arranged in a linear or sequential manner, where each element has a direct predecessor and successor (except for the first and last elements). Some common linear data structures include:

Arrays: A collection of elements of the same data type, stored in contiguous memory locations and accessed using an index.
Linked Lists: A collection of nodes, where each node contains data and a reference (or pointer) to the next node in the sequence.
Stacks: Follows the Last In, First Out (LIFO) principle, where elements are added and removed from the same end, called the top.
Queues: Follows the First In, First Out (FIFO) principle, where elements are added at the rear (enqueue) and removed from the front (dequeue).

Trees (Binary Trees, Binary Search Trees, etc.)
Graphs (Directed, Undirected, Weighted, etc.) Implementation of User-Defined Data Types in C++: **1. **Rational Number:**** class RationalNumber { private: int numerator; int denominator; public: RationalNumber(int num, int den) : numerator(num), denominator(den) { // Simplify the rational number int gcd_val = gcd(numerator, denominator); numerator /= gcd_val; denominator /= gcd_val; } int gcd(int a, int b) { while (b) { a %= b; std::swap(a, b); } return a; } void print() { std::cout << numerator << "/" << denominator << std::endl; } }; 2. Complex Number: class ComplexNumber { private: double real; double imag; public: ComplexNumber(double r, double i) : real(r), imag(i) {} void print() { std::cout << real << " + " << imag << "i" << std::endl; } }; **3. **String (Custom String Class):****

class MyString { private: char* str; public: MyString(const char* s) { str = new char[strlen(s) + 1]; strcpy(str, s); } ~MyString() { delete[] str; } void print() { std::cout << str << std::endl; } };

*4. Matrix:**** class Matrix { private: int rows; int cols; int data; public: Matrix(int r, int c) : rows(r), cols(c) { data = new int[rows]; for (int i = 0; i < rows; i++) { data[i] = new int[cols]; } } ~Matrix() { for (int i = 0; i < rows; i++) { delete[] data[i]; } delete[] data; } void set(int r, int c, int val) { data[r][c] = val; }

Data Management Concepts and User-Defined Data Types in C++, Study notes of Data Structures and Algorithms

Related documents

Partial preview of the text

Download Data Management Concepts and User-Defined Data Types in C++ and more Study notes Data Structures and Algorithms in PDF only on Docsity!