09. Functional Programming & Pure Functions - Java Interview

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Functional programming is a programming paradigm that emphasizes the use of pure functions to perform computations. In contrast to imperative programming, which relies on statements that change a program's state, functional programming is based on expressions that evaluate to a value. Pure functions are a key concept in functional programming, and they have several advantages over impure functions.

In this video, we will explore functional programming and pure functions in the context of Java. We will begin by defining what functional programming is and how it differs from imperative programming. Then, we will explain what pure functions are and how they are used in functional programming.

Functional programming is a programming paradigm that is based on the concept of functions as first-class objects. This means that functions can be assigned to variables, passed as arguments to other functions, and returned as values from functions. In functional programming, the focus is on composing functions to create complex behavior, rather than on writing procedural code.

One of the key advantages of functional programming is that it can lead to more modular and reusable code. Since functions are independent units of behavior, they can be easily combined and reused in different parts of a program. Additionally, since functions do not rely on mutable state, they are less prone to bugs caused by unintended side effects.

Pure functions are functions that have no side effects and always return the same output given the same input. In other words, pure functions are deterministic and have no observable effects outside of their own scope. Pure functions are a key concept in functional programming because they make it easier to reason about the behavior of a program.

In Java, pure functions are defined using the "final" keyword to indicate that they cannot be overridden or modified. Pure functions in Java typically take inputs as arguments and return outputs as return values, without modifying any state outside of their own scope.

We will provide several examples of pure functions in Java, including a function that calculates the factorial of a number, a function that computes the sum of a list of integers, and a function that returns the nth Fibonacci number. Each of these functions is pure because it takes inputs as arguments and returns an output, without modifying any state outside of its own scope.

We will also discuss how to write pure functions in Java using the Stream API, which provides a functional programming interface for working with collections of data. We will provide several examples of how to use the Stream API to perform common operations such as filtering, mapping, and reducing.

Finally, we will discuss some of the challenges and limitations of functional programming in Java. While Java is not a pure functional language, it does provide many features that can be used to write functional-style code. However, there are still some limitations to what can be accomplished with functional programming in Java, such as the inability to define higher-order functions or use pattern matching.

In conclusion, this video will provide an introduction to functional programming and pure functions in Java. By understanding the concepts of functional programming and pure functions, developers can write more modular, reusable, and bug-free code. Additionally, the techniques presented in this video can be used to improve the performance and scalability of Java applications.

Kywords:
Functional programming, Pure functions, Java, Programming paradigm, Expressions, First-class objects, Modularity, Reusability, Immutable state, Deterministic, Side effects, Final keyword, Inputs, Outputs, Scope, Factorial, Sum, Fibonacci, Stream API, Collections, Filtering, Mapping, Reducing, Higher-order functions, Pattern matching, Performance, Scalability, Bug-free code, Imperative programming, Procedural code, Composition, Behavior, Mutable state, Observability, Abstraction, Lambda expressions, Function composition, Laziness.