Functional Programming

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Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. In simpler terms, it is a way of writing software applications using only pure functions and immutable values.
Here are a few key characteristics of functional programming:
Pure Functions: A function is considered pure if it always produces the same result for the same input and doesn't have any observable side effects. This deterministic characteristic makes it easier to reason about the program's behavior.
Immutability: In functional programming, data is immutable, meaning once a data structure or variable is created, it cannot be changed. If you need to modify some piece of data, you create a new data structure or variable.
Higher-Order Functions: Functional programming languages support passing functions as parameters to other functions and returning them as the results. Higher-order functions are a direct consequence of the fact that in functional programming, functions are first-class citizens.
Recursion: Because functional programming discourages statements and looping constructs, recursion is often used as a substitute for iterating over sequences or repeating computation.
Referential Transparency: A property of a function where its output is solely determined by its input and there are no side effects. This property allows programmers to replace a function call with its resultant value without changing the behavior of the program.
Statelessness: Functional programming avoids shared state, mutable data observed in many Object-Oriented Programming languages.
Functional programming languages include Haskell, Clojure, Scala, Erlang, and Lisp, among others. JavaScript also supports functional programming.
The functional programming paradigm can result in programs that are more efficient, easier to debug and test, and suitable for solving complex problems, especially in parallel and concurrent computing contexts. However, it also often requires programmers to think more abstractly about the problem they're solving, which can be challenging.

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