Functional programming in software solutions has long been part of software development. Recently, however, available programming has taken on even greater significance within modern development practices, and this article looks into its concepts and practical examples in JavaScript and Java.
What Is Functional Programming?
Functions are central to code organization; they appear across all higher-order programming languages. Functional programming refers to using parts for maximum impact when developing clean and maintainable software products; more precisely, it represents an approach or paradigm used when writing code.
Functional programming can sometimes be confused with object-oriented programming (OOP) and procedural programming, although that would be misleading as these approaches do not conflict; most systems incorporate all three. Functional programming offers clear advantages in tips to boost programming skills for certain situations and is increasingly adopted into modern software trends. Available programming should form part of every developer's conceptual and syntactic toolbox to give them an advantage in developing.
Pure Functions
Functional programming strives for what is known as pure functions; that is, functions whose results depend solely on input parameters without initiating side effects other than returning value.
Pure functions are elegant in their architectural simplicity. Reducing complexity to just its arguments and return value (API) may appear dead ends: their sole interaction with external systems comes through its defined API. Contrast OOP, where object methods interact directly with object members (object members), with procedural style code where external states may often be altered from within functions.
Immutability
Functional programming philosophy stipulates that functions should not alter data outside the process. In practice, this means not changing input arguments of functions; the return value should reflect work done instead - helping avoid side effects while making it simpler to reason about their effects within larger systems.
First-Class Functions
Functional programming moves beyond its ideal of pure function usage to include first-class functions as crucial building blocks in reality. A first-class function can be seen as a "thing in itself," capable of standing alone and being treated separately; such an approach leverages language support by using variables, arguments, and return values from functions for creating elegant code.
As first-class functions can be so flexible and helpful, even highly OOP languages such as Java and C# have added support for them in recent versions of these programming languages, which led them to implement Lambda expression support in Java 8.Functions as data are another way of characterizing first-class functions. That means they can be assigned directly to variables like any other data item would.
Higher-Order Functions
Higher-order functions (functions that operate upon functions) are known to accept another function as their argument and return another function, respectively.
Both JavaScript and Java have recently introduced improved function syntax; Java's latest software editions are the arrow operator and double colon operator, while in JavaScript, there was only the latter. All three operators make it simpler for users to define and utilize functions efficiently - such as anonymous functions that don't receive reference variables as their parameters.
Why Functional Programming Matters
Functional Programming has traditionally been less prevalent than its object-oriented programming counterpart, yet has seen a recent surge in usage due to machine learning and big data's rise. Functional programming stands out by efficiently parallelizing pure functions - something machine learning and big data cannot do efficiently enough with their current methods of working with data analysis workflows and tasks. Functional programming makes code easier to analyze, test, maintain, and debug for this analysis workflow and tasks.
FP's pure nature makes it an ideal candidate for data analysis and machine learning applications. Pure functions always generate consistent outcomes without outside variables altering them significantly.
Algorithms created using functional programming (FP) allow programmers and software developers to quickly detect and correct errors within an algorithm, while their pure functions simplify debugging. Many prefer working in this programming paradigm over working with something like C or Java due to all their potential hurdles in debugging them. Functional programming will play an essential role in future tech development because of its modular nature. Modularity breaks up large projects into manageable modules that can be tested individually to reduce unit testing and debugging time and effort.Functional programming languages offer two innovative forms of glue -- higher-order functions and lazy evaluation -- which enable modularization programs in new and valuable ways," according to Hughes' paper.
Benefits Of Functional Programming
Functional programming continues to offer significant advantages even among developers familiar with object-oriented development; some notable benefits are:
Best Programming Practices: Functional programming requires coders to abide by stringent constraints that compel them to write in specific ways; practical programming forces engineers to adopt good programming practices like modularity or creating programs with smaller components.
Clean Code: Given that functional programming combines pure functions with organized components that work with one another, the code is reasonably clean. Everything does precisely what it needs to do, which, in turn, helps in organizing the codebase.
Modular Code: Modular code has become one of the best practices because its small functions make reusing them much more straightforward, without fear that changes in other parts would change their work or affect them negatively.
Robust Programs: Functional programs tend to be more reliable from a mathematical viewpoint than other applications due to having fewer moving parts (mutable variables and hidden states) than traditional ones, making functional programs more straightforward and increasing efficiency.
Easy Debugging: Functional programming ensures you always know who does what. Since data and functions do not change over time, you can pinpoint any module responsible for issues when debugging quickly.
Computational Efficiency: Utilizing functions allows you to distribute them across multiple cores without worrying about multithreading programs, thus taking full advantage of those cores for increased computational efficiency in your programs.
Functional programming's great appeal lies in its breadth of benefits, all without abandoning other programming paradigms or languages altogether. That is because applicable principles exist across most non-functional languages, making it simpler and quicker for developers to reap them. You could always opt for an exclusively available language to boost them further, but, generally speaking, doing so would likely prove unnecessary in practice.
The 6 Most Popular Functional Programming Languages
Haskell
Haskell is an all-purpose, functional programming language. Every function can be considered pure mathematical functions; statements and instructions do not exist, and expressions that do not modify variables (local or global) nor access state (for instance, random numbers or time) cannot be written within Haskell programs.
Erlang
Erlang (Erlang/OTP) is a general-purpose functional programming language widely employed for soft real-time systems with high availability requirements, such as eCommerce stores, computer telephony networks, and instant messaging applications.
Clojure
Clojure is an intuitive functional-dynamic dialect of Lisp for Java that combines highly organized infrastructure and interactive script development for an expressive scripting language. Clojure excels at multithreaded programming environments.
Common Lisp
Common Lisp is an offspring of the Lisp family of programming languages and an ANSI-standard multiparadigm programming environment (supporting functional, procedural, and object-oriented paradigms). Common Lisp also has a robust macro system that allows programmers to customize it to their own application requirements.
Scala
Scala is an all-purpose programming language supporting OOP and functional programming paradigms. Static types provide extra protection in complex applications, while JavaScript/JVM runtimes allow programmers to develop dynamic systems supported by ecosystems of libraries.
Elixir
Elixir is a functional general-purpose programming language ideal for developing scalable and maintainable apps using Erlang Virtual Machine technology which facilitates low-latency systems that run fault-tolerant distributed environments. Elixir's widespread adoption can be seen across custom software development services, web design, and multimedia processing applications, among many others.
Object-Oriented Programming vs Functional Programming
One key distinction between object-oriented and functional programming lies in their respective imperative versus declarative programming models.OOP employs the imperative programming model, in which functions must always be coded for each step needed to solve a problem. You specify this within each operation coded; therefore, this model forces programmers to understand which functions they require to effectively solve specific issues rather than depending on models that can do this.
FP employs declarative programming models, meaning they rely on the concepts underlying a programming language to execute steps toward reaching an outcome predefined beforehand. Imperative programs focus on solving problems step-by-step, while declarative ones assess the results of such endeavors.
Read More: Developing Software Solutions with the Internet of Things
Another key difference lies with data mutability; OOP uses mutable while functional programming utilizes immutable. You may change or modify (mutate) objects created via OOP after creation, while this option cannot be done for immutable ones; to maintain flexibility within functional programming, you may make copies of those objects and write your code using those copies instead of altering or changing directly the thing being coded upon itself. Overall, immutable code is easier to update, more cost-efficient to manage, more straightforward to test and debug, and more accessible to comprehend due to fixed variables being easy for programmers and software developers alike to reason about. Many programmers and software developers prefer working with functional programming models (FP).
At its core, selecting the appropriate programming paradigm depends on your intended application. OOP works better for standard projects with limited requirements, while functional programming (FP) excels when used for scalable and flexible solutions.
With Functional Programming, Less Is More
Functional programming can best be understood from over 50 years: in the late 60s, structured programming emerged as an alternative paradigm aimed at increasing code quality while decreasing developments in technology times - it became known by this name.
Multiple languages began facilitating structured programming while existing ones were modified to make structured programming possible. One of the most striking characteristics of structured-programming languages was not one feature but its absence: that being GOTO.GOTO is used to redirect program execution. Instead of directly carrying out each statement in sequence, the flow is diverted towards one specified in GOTO rather - often when certain conditions have been fulfilled or satisfied.
Programmers decided to remove GOTOs due to what they had discovered from using them: it made programs difficult for humans to comprehend. Programs using GOTOs are often called spaghetti codes because their execution could resemble one long thread from spaghetti in an otherwise straightforward order of instructions.Developers needed help comprehending how their code worked or why it sometimes didn't. According to software experts of that era, GOTO statements created unnecessary complexity that needed to disappear.
Back then, this idea was novel and many programmers objected to losing such an essential statement as GOTO (goto). The debate went on for over ten years. Still, eventually, it died out, and no one ever advocated its return - as its absence significantly decreased the complexity and increased reliability of software produced through more limited programming languages, thus helping programmers more readily comprehend what code they were writing and reason about its meaning more quickly. Today nobody would argue for bringing back GOTO.Even though modern higher-level language models no longer utilize GOTO statements, software continues to increase in complexity and fragility. When considering how to modify programming languages to prevent frequent mistakes, software designers may draw inspiration from those in the hardware industry.
Nullifying Problems With Null References
Resistors cannot be shared between the keyboard and monitor circuitry on a physical computer. Yet, programmers frequently employ this strategy in software coding as shared global state variables that multiple processes may change simultaneously.
Imagine running your microwave every time it ran, and your dishwasher settings changed from Normal Cycle to Pots and Pans without you realizing. While that might never occur in real life, software often does. Programmers write code-calling functions expecting them to perform one function only, but many parts have side effects that alter the global state, leading to unexpected results. Hardware doesn't offer as many opportunities for missteps as software because its laws limit what's possible. Engineers still make errors occasionally but not nearly so frequently as in software, where too much could go wrong at any given point in development.
Null references, another complexity monster lurking within software development, refers to memory locations where there's nothing there when used as references; any attempt at reading or changing these points of reference results in errors that require programmers to check whether something references nothing. Therefore, programmers need to remember to check first whether something references anything null before reading or changing anything referencing them. Nearly every popular language today suffers from this weakness. Tony Hoare introduced invalid references into ALGOL in 1965, and their use was later adopted into other languages. At first, Hoare did it to implement them quickly but now sees this practice as a costly oversight causing numerous bugs when an expected reference invalidates.
Software developers must be highly disciplined when developing code, sometimes resulting in avoidable pitfalls for software development teams. The architects of structured programming knew this to be true regarding GOTO statements, leaving developers no chance for escape when writing GOTO-free code promised by these languages. They knew GOTO statements had to go to guarantee improved clarity for code users.
Avoiding Null-Reference Surprises
Functional programming offers another solution to Hoare's "billion-dollar mistake," null references, by disallowing their usage altogether and replacing them with Maybe (or Option in some languages), an object capable of representing nothingness or just some value. Working with Maybes forces developers to constantly consider both possibilities - something null references do not do - thus eliminating many bugs they cause in code development and testing environments.
Functional programming also demands data immutability, meaning once variables have been assigned a value, they stay there forever. Variables operate similarly to mathematical variables: when computing formulae such as y = x2 + 2x - 11, an initial value for x is selected at no point during computation that changes, so this same value is used throughout. Most programming languages don't impose such limitations: once computed with one value, you may modify its value before calculating 2x; by forbidding developers from changing values midway through calculation, they can follow similar reasoning techniques that middle school algebra class uses!
Functional programming languages differ significantly from most others in that their roots run deep within mathematics; this special connection gives available languages some advantages over their more standard counterparts. Why does that occur? Because people have been developing mathematics for millennia. Instead of this, programming paradigms like object-oriented programming (OOP), which have only seen development over recent decades and decades at most, are cruder and immature in comparison.Imagine this: every time your microwave ran, its settings changed from Normal Cycle to Pots and Pans cycle - in software, this happens all the time!
Functional programming involves writing code using expressions rather than statements; math skills learned during middle school can now be employed when writing available languages like Python.
Functional purity allows us to reason about code using algebraic substitution in the same way, we analyzed equations back in algebra class to reduce code complexity efficiently and concisely. Non-functional languages (imperative languages) do not offer similar mechanisms for deducing how code operates, and thus, we have no way of reasoning how our program works.
Issues Of Functional Programming
Functional programming may seem to be an ideal framework, but its imperfections must be noticed. Purely available programming is challenging in practice because developers frequently resort to other paradigms to get their programs to perform the way they expect. There may also be issues surrounding the following:
- Easy To Break: Functional programming can be so intricately designed that developers must tread lightly when applying it, adhering to very stringent applicable requirements that must always be adhered to, failing which the application fails and stops functioning as designed.
- Code Can Be Hard To Read: Functional programming offers clean and organized code; however, its high degree of abstraction often makes it hard to decipher the code's actual intention - particularly with projects that heavily utilize functional libraries or point-free syntax.
- Steep Learning Curve: Functional programming's roots lie deep within mathematics, making it hard for newcomers to grasp its conventions and practices fully. Furthermore, available programming involves specific terminology (like "pure functions" and "referential transparency"), which requires years of study to grasp completely.
- Complicated Function Integration: Building specific features using pure functions can be straightforward once you know how, yet integrating pure tasks into a more extensive application remains challenging due to having to come up with ways for these "pure" (no side-effect) functions to work together efficiently to reach their goal (which may prove challenging due to pure functional programs' unwillingness to accommodate I/O components).
- Lack Of Recursive Loops: While loops are viral for a good reason - they greatly simplify iterative tasks. At the same time, functional programming doesn't use them, forcing developers to rely on pure recursion, which might feel unfamiliar or overwhelming to many users.
Functional Programming's Future
My company is small. We deliver software to government agencies to enable veterans to obtain benefits from the United States Department of Veterans Affairs, making this work very satisfying but not particularly lucrative; due to these slim margins, we must use every tool at our disposal to do more with fewer developers - functional programming being one such approach that works beautifully here.
Unglamorous businesses such as ours often need help to recruit top developers. Now we are taking an innovative approach by hiring developers interested in working on functional codebases; being ahead of this trend enables us to attract talent that many similar-sized firms could only dream about acquiring.
Assuming pure functional languages become mainstream in software engineering, they will increase quality and robustness while significantly cutting time wasted hunting down bugs that cannot occur with functional programming alone. While available programming doesn't work like magic, I am reminded how fortunate I am every time I must deal with non-functional codebases.One indicator that the software industry is gearing up for a paradigm shift is when functional features appear increasingly often across mainstream languages. Making such changes will take more work on behalf of the industry, and its benefits should make the transition worthwhile; that seems likely where things will head next.
Summing Up Functional Programming
Functional Programming's increasing relevance within the software industry has been brought home here by this blog, emphasizing first-class, pure, and immutable functions being encouraged as solutions to fragility and complexity in production systems. The benefits of functional programming for machine learning projects or large data projects include modularity, clean code, and efficient data analyses that result in efficient analysis. Although available programming remains challenging for some to use efficiently, mainstream languages that incorporate functional features are witness to its increasing presence as an industry standard, and this trend towards available programming could increase software robustness and quality!
