Efficient and successful programming forms the basis of most things that are found on the Internet. Various methodologies have the sole aim to ensure code that is understandable, manageable, and can run free of any bugs. The two most common and essential programming methodologies are Object-Oriented Programming and Functional Programming.
OOP vs Functional Programming
The main difference between OOP and Functional Programming is that OOP is a type of imperative programming model while Functional programming is a type of declarative programming model. The key elements in OOP are objects and methods while the key elements in functional programming are variables and functions.
OOP stands for Object-Oriented Programming. It is a conceptual technique of programming that operates on the usage of objects as the key. The main features of OOP are abstraction, inheritance, polymorphism, and encapsulation.
On the other hand, functional programming is a technique of programming with functional factors and accentuates the creation and implementation of programs. The basis of functional programming has various concepts like Pure Function, Type Systems, High Order Functions, Recursion, Referential Transparency, and Strict and Non-Strict Evaluation.
Comparison Table Between OOP and Functional Programming
|Parameters of Comparison||OOP||Functional Programming|
|Definition||It is a programming Paradigm that emphasizes object-oriented concept||It is a programming paradigm that emphasizes the usage of functions for performing specific tasks|
|Importance||OOP gives importance to data and not to the procedures||Functional programming gives importance to functions and not to the data|
|Parallel programming||Parallel programming is not supported in OOP||Parallel programming is supported in functional programming|
|Data hiding||OOP has data hiding and secured programs can be created||Functional programming does not provide any data hiding and hence no security is provided|
|Integration of new data||Addition and integration of new data and functions can be done through an easy process||Addition and integration of new data and functions is difficult in functional programming|
What is OOP?
OOP is the short-term for Object-Oriented Programming. It is a paradigm of programming which is solely based on the concept of objects. OOP can contain the data in the form of properties and attributes which are also commonly known as fields. The code is contained in the form of methods or procedures. A distinguishing feature in objects is the accessibility and modification offered to the procedures of the objects for the data fields.
OOP has designed programs with objects and even can interact with one another. The languages in OOP are diverse. The most popular languages of OOP are class-based which simply implies that the objects are instances of the class. This also becomes a determining factor for types. OOP Collects the objects for the programmer to identify and manipulate.
There are various programming languages that supports OOP like Java, C++, Python, Visual Basic.NET, MATLAB, Objective-C, SIMSCRIPT, Object Pascal, SmallTalk, Common Lisp, and others. They form the multi-paradigm. The introduction of Simula formed the basis of OOP. This programming language was mainly involved in the physical modeling of OOP. The two most compatible languages of OOP are Ruby and Python. Both languages are beneficial for data abstraction.
OOP is useful for developers who Have an intent to manipulate and do not require logic to manipulate the object. The type of programming is most suitable for complex large and actively updated programs with regular maintenance. It also includes programs for designing manufacturing and even mobile applications that work under simulation software.
What is Functional Programming?
Functional programming is a paradigm of programming that constructs programs by composing and applying functions. The programming type is declarative where the definition of functions are trees of expression and do not have any sequence of imperative statements. The definitions map values to other values. The treatment of the functions in functional programming is as first-class citizens.
Functional programming has the programs written in a style that is composable, declarative, and has the combination of small functions in a modular manner. The programming type is considered synonymous with the programming of purely functional. Purely functional programming is considered a subset of functional programming. The treatment of the functions is as pure functions or deterministic mathematical functions.
The roots of functional programming are mainly in academia which has evolved from Lambda calculus. The popularity of functional programming in history is comparatively less than imperative programming. However functional programming is mainly used in education and industry in the current time. Examples – Haskell, Common Lisp, Racket, Wolfram Language, F#, Scheme, Erlang, Clojure, OCaml, and Elixir.
Main Differences Between OOP and Functional Programming
- Iteration in OOP is done by the usage of loops while iteration in functional programming is done by the usage of recursion.
- The fundamental elements of OOP are methods and objects while the fundamental elements of functional programming are variables and functions.
- The data in OOP is in mutable form while the data in functional programming is in the mutable form.
- The programming model of OOP is an imperative programming model while the programming model of Functional Programming is a declarative programming model.
- OOP has provision for three access specifiers which are Private, Public, and Protected while functional programming does not have provision for any access specifier.
OOP and functional programming are the two most popular programming methodologies that are used in most languages both the methodologies have distinct approaches to manipulate and store the data.
The model basis of both the methodologies is also different from each other. The key elements are different so the developers can use the methodologies for different applications. The developers need to evaluate both the methodologies before application, to gain maximum output.