"Understanding basic Programming concept: Types, Data Types, Data Item, Classes, Objects, Method, ADTs, and Data Structures Explained."
In the world of programming, several fundamental concepts are crucial to understand. Types, data types, ADT, data items, class methods and Objects are often used interchangeably, but they have distinct meanings and roles. In this blog post, we'll dive into these concepts, clarify their differences, and shed light on their significance in the programming landscape.
Types:
Types are the foundation of data in programming. They represent a collection of values that share specific characteristics. However, it's important to note that these characteristics can vary from one programming language to another. For example, Java has a Bytes Type, which is absent in languages like C++. Types define what data can exist in your program and serve as a blueprint for data structures.
Data Types:
Data Type is just a Type with a collection of operations to be performed on that Type. For example, a list data type might be an Array type with some operations like pop, add, get, and delete on the elements of the Array and it might also be implemented using a linked list. The main difference between a type and a data type is that Type only specifies the value, while Data types include both the values and the operations that can be performed on such values. It is important to note that when we refer to data type it contains both the value and the operation/method on the value.
This is the content of the string(str) data type in Python. It contains a list of operations in the form of methods that can be performed on the str data type. From this, it clearly visible that type is just the value while the value and the operation on the value are called Data type.
Data Items:
Data items are individual pieces of information that belong to a specific data type. For example, the value "False" is a data item belonging to the boolean data type. Data items are crucial as they populate data structures and enable the execution of operations defined for a particular data type.
Abstract Data Types (ADT) and Data Structures:
Abstract Data Types (ADTs) and Data Structures are closely related but distinct concepts.
Abstract Data Type (ADT): ADTs define a high-level concept of a data type along with its operations. They are abstract and do not specify implementation details. For example, a Stack ADT specifies operations like push and pop without specifying how these operations are implemented.
Data Structure: A data structure is the concrete implementation of an ADT. It determines how the ADT's operations are carried out. Multiple implementations can exist for a single ADT. For instance, a Stack ADT can be implemented using a linked list or an array, depending on the problem's requirements and constraints.
When choosing an implementation for a data structure, it's essential to analyze the problem and consider factors like the required operations and resource constraints.
Classes and Objects:
A Class is a very powerful concept in Object-Oriented programming, and it is impossible to talk about OOP without talking about classes. Classes are a kind of reference, mould, or factory that defines what values and operations on those values an instance of that class can have. An instance of a class is known as an Object.
Let's use a concrete example. The company that makes a laptop, say Acer Nitro 5, has some mould or generalized format that specifies how a Nitro 5 laptop should look like. That is exactly what is known as a class, while each physical Acer Nitro 5 laptop, like the one I am currently using, is the Object of the class or known as the instance of a class. One thing to note is that a class does not allocate memory for itself, while the object that is created from the class is allocated a block of memory depending on the size. The main purpose of OOP is to give programmers the power to represent real-world objects easily and also the ability to bind a Type together with operations on the type.
One very important thing I have realized while working with different languages is that though the idea of OOP is similar in all languages, the implementations sometimes differ, and sometimes some languages might have some OOP concepts that are not in other languages. For example, Python's philosophy is that everything is an Object or otherwise an instance of a class. So data types like int, tuple, and dictionary are just all classes. We can see that in Python, all Data types are classes. Language like Java doesn't support multiple inheritance for classes, though it offers the flexibility of implementing multiple interfaces. This design choice allows Java developers to achieve similar goals, such as inheriting behaviour from multiple sources, by using interfaces. OOP in C++ has virtual keywords while it is absent in Python or Java OOP.
Before moving on, I intentionally did not say that Class is a kind of template because a template is another thing entirely in C++. So, looking from the context of C++, it would be incorrect to say that classes are a kind of template. This is very important to note as many software who do not use C++ are prone to say that class is a kind of template.
Note:
In certain scenarios, some of these terms might be used interchangeably. For instance, in Python, a data type is represented by a class. Therefore, it is permissible to refer to it as both a class 'int' or a data type 'int.'
Conclusion.
Understanding these fundamental concepts is essential for anyone venturing into the world of programming. Each concept serves a unique purpose and contributes to the structure and functionality of your code. Whether you're working with types, data types, abstract data types, data structures, classes, or objects, a solid grasp of these concepts will greatly enhance your programming skills.
Image 1 credit:- EDUCBA