Functional programming has existed for the last six decades, but so far, it hasn’t ceased to overcome the general use of object-oriented programming. With the explosive growth of machine learning and big data, functional programming has been gaining popularity because of the simplicity at which pure functions can be parallelized, which leaves more people wondering if functional programming the future again. Code for data analysis tasks and workflows are also easier to follow, test, and maintain using the functional paradigm, lending to its growing future use.
Even object-oriented programming languages like Java and Python have adopted enormous concepts from functional programming like built-in map, filter, and reduce functionality. They also can declare pure in-line lambda functions and creation of first-class and higher-order functions to pass in functions as parameters.
Simply put, functional programming entails building pure functions for fixed variables and changing states through their responses. In contrast, other programming languages can change the application state by mutating variable references from within a program. You can learn about more of the differences between functional programming and object-oriented programming in this article.
Because of its pure nature, functional programming is impressive for coveted tasks like machine learning and data analysis. However, that doesn’t mean you should ditch other programming languages and go completely functional as each programming languages has tasks it does better than others. But, it is vital to learn the basic principles to apply them to your advantage when necessary. It’s for these reasons functional programming is termed the future, but maybe more the future of machine learning and big data then all of software development.
Is Functional Programming the Future?
Functional programming is a programming paradigm that treats computation as evaluating mathematical functions. It is a programming style that emphasizes using functions to perform calculations rather than using imperative statements to change a program’s state. This approach has several benefits, including making it easier to reason about code, easier to test and debug, and easier to parallelize and distribute computations.
But is functional programming the future? It’s hard to say for sure, but there are certainly a lot of proponents of functional programming who believe that it is the way of the future. One argument for functional programming is that it is more scalable and easier to maintain as the codebase grows. This can be a significant advantage with the increasing complexity of software systems.
However, it’s important to note that no single programming paradigm is a silver bullet. Different approaches are better suited to different tasks, and developers need to be able to choose the right tool for the job. So while functional programming may be the future for some projects, it’s unlikely to completely replace other programming paradigms.
And let’s not forget the humor factor. Some functional programming enthusiasts have been known to jokingly refer to themselves as “functional fanatics” and to refer to non-functional programming as “imperative programming,” as if it were some kind of archaic, barbarian practice. So if you’re considering a career in functional programming, be prepared for some good-natured ribbing from your colleagues!
With that in mind, let’s look at why software developers are falling in love with functional programming making it an integral part of computer science in the future. Let’s also consider some of the features of objected oriented programming to see if functional programming can replace it entirely. Spoiler: the two will likely co-exist in software development and even in the same application.
Use of Pure Functions
Pure functions repeatedly generate the same result and have no outside values influencing the end-result. Due to this feature of pure functions, algorithms created using functional programming are effortless to identify and correct errors.
Pure functions typically adopt the mathematics-solving methodologies. For instance, if you key in 3+3 in a calculator, the answer will be 6. The same applies to pure functions. There are no external elements involved, therefore rendering the functional programs pure. An example would be an inline lambda function that takes n as input and returns n + n.
Debugging is a chronic issue for both the programmers and the developers, and that’s why they are switching to functional programming because its programs are easy to debug due to the use of pure functions.
The utilization of pure functions makes functional programming completely transparent. The notable distinction between pure and impure functions in functional programming languages remarkably improves these programs’ transparency.
Besides, pure functions work exclusively without factoring in external elements. That means they only work with the users’ entries. In contrast, non-functional programming languages factor in extra inputs and return outputs somewhat different from the user’s information.
Since no external elements are involved in functional programming, the algorithm doesn’t deviate from the user’s input. Therefore, regardless of the output, it conforms with the information and has no sinister aspect.
Functional programming offers a variety of benefits, including improved readability of values. The use of pure values means their state remains unchanged till the end. The values also enhance program readability, making it a no-brainer for the developer to grasp the code.
Since most functional programming languages are high-level, and the users take every function as a value, it is effortless for developers to recall the functional program and ultimately incorporate those values into other functions.
In layman’s language, a variable is something that keeps changing from state to state. However, this is the opposite of functional programming.
Here, the programmer/developer cannot doctor the variables immediately; it has been instigated. One may be of the perception that the constancy of variables coupled with recursion could result in a decline in performance.
However, it is necessary to comprehend that this feature ensures the program is unaltered till the end. Along with the valuable protection that functional programming renders by using pure functions, this methodology makes functional programming languages superior to their counterparts in matters of security.
Security being a key element in software development has prompted developers to switch to functional programming to better their system security.
Seamless Parallel Programming
Functional programming is typically reckoned for its capacity to develop complete parallel programs. Undeniably, developing applications is one of the most reckoned use scenarios, especially among developers who have adopted functional programming.
The main factor behind this is the static application of variables in various functional programming languages. Because pure functions don’t modify the variables and work only on the user inputs, it becomes less complex to handle parallelism.
Moreover, considering the programs’ improved dependability, the room for error is significantly reduced, enhancing the program’s efficiency.
Validating Functional Signatures
Signature validation is a critical aspect of software development. Functional programming is highly rated for its ability to make functional signatures extremely valid and worthwhile when contrasted to other ways that exclude functional programs. The pure variables of functional programming language ensure the signatures outline all the information about a function’s working alongside their argument details and other necessary details.
Furthermore, this is another practical reason why functional programming is the future of software development.
As a functional programming language, Scala allows developers to write code in both OOP and FP (functional programming). Scala mainly focuses on writing software using exclusive pure functions and constancy values. This language is in the process of becoming fully functional.
Why functional programming won’t deprecate object-oriented programming
Object-oriented programming (OOP) has become a critical component of software development. Despite introducing numerous programming languages such as C++ and Java, developers looking to develop mobile software must grasp an object-oriented approach. The same applies to intricate web development, considering the popularity of OOP languages such as PHP and Python.
Some IT professionals feel that object-oriented programming is obsolete; thus, grasping its concepts is a complete waste of time. They find it illogical to use objects instead of the top-down methodology of traditional programming in languages such as Visual Basic.
If you have coded this type of software, you’re possibly accustomed to breaking complex problems into less-complex problems and solving them separately in code units. If you grasp functional programming, which views code elements as proper mathematical functions and prohibits them from doctoring other aspects, i.e., the output reflects the user’s input.
Despite the rise in the popularity of functional programming, object-oriented programming is still in use. Some of the reasons why functional programming has not deprecated OOP include the following:
Reuse of code through inheritance
Suppose one guy wants a metallic table object in addition to your table object, and another requires a glass object. Everyone builds their objects singly but realizes similarities among them. Every object is simply a different type of table. This is where the inheritance method proves to save time. Here you need to create one generic table class and then define the metallic and glass subclasses to adopt the generic features.
Certainly, Metallic and glass tables have their distinctive qualities and functions. Since there are similarities between the two, the two inheriting classes can reuse the prevailing code rather than writing these functions once more.
If, for instance, you want to make changes to all the table objects, irrespective of the type, you need to make adjustments to your table class, and all the table objects will adopt the new code. That’s why some developers still prefer OOP over functional programming.
Flexibility via polymorphism
Based on the above example, you don’t need a lot of functions to get started. For instance, metallic and glass objects share some commonalities, but they have other unique traits.
This is where polymorphism comes into play. This is because a single function can inherit the traits in the parent class. For instance, the parent Table class called ‘maintenance’ would work with MetallicTableMaintenance and GlassTableMaintenance. This is where polymorphism seems pivotal in software development.
Effective Problem Solving
A programming language like C has a decent reputation in the programming world, but developing software in a top-down language is highly discouraged unless you’re comfortable with it. This is because there are higher prospects of project collapse due to complexities. On the other hand, writing a program in a functional programming language such as Haskell or ML can be routine.
Object-oriented programming is typically the most natural and sensible approach once you use it. OOP languages allow developers to split your software into medium-sized problems that can be solved independently.
Data Abstraction doesn’t display the trivial elements to the user; instead, it only shows essential details. For instance, a car is considered a vehicle instead of its parts.
Data Abstraction is the process of pinpointing only the indispensable traits of an object overlooking the irrelevant details. The features and properties of an object set it apart from other objects sharing similarities to aid in classifying/grouping objects.
Take the example of a typical person operating a computer. He knows that pressing the power button will turn on/off the computer, but they typically don’t know the PC internal mechanisms that power on and off the PC. This is the power of abstraction.
In OOP programming languages, abstraction is realized through interfaces and abstract classes. It is possible to achieve 100% abstraction via the use of interfaces.
Functional programming, though preferred over object-oriented programming for immutable code and concurrency, is far from deprecating OOP. As seen above, code reusability, data abstraction, practical problem-solving, and flexibility in polymorphism are only achieved via object-oriented programming. So since some code lends itself more naturally to object-oriented programming, there are other use cases where functional programming would be better, such as machine learning, where functions need to be used as delegates for parallel processing. In this situation, it is imperative to have an immutable and pure function to ensure data consistency between threads or distributed hosts in the case of spark.