Reducing code complexity with functional programming

In this article, We will walk over a simple exercise which will help me to communicate my thought clearly

Suppose, we have a class Person as below

class Person {
    name:string
    age:number
}

Now, our task is to find all adult person’s name which means find all person’s names who has age gather than 17 years.

Let’s first do it object-oriented way and you will end up with a function something like below

function findAdultPersons(persons:Person[]):string[] {
    const names = []
    for(const person of persons) {
        if(person.age>17) {
            names.push(person.name)
        }
    }
    return names
}

Now, Going with the functional programming way you can re-write the function as below

function findAdultPersons(persons:Person[]):string[] {
   return persons.filter(person=>person.age>17).map(person=>person.name)
}

Okay, Let’s move ahead.

You might have heard different ways of computing code complexity. A couple of such methods are listed below

• Cyclomatic complexity
• NPath complexity

You can find more details about both of them in this article.

For the sake of simplicity, we will consider Cyclomatic complexity for our scenario as it is really easy to calculate. The Object-oriented findAdultNames has complexity value 3 whereas functional programming way findAdultNames has complexity value only 1 which is 66% lower compared to the object-oriented approach

Here, one can argue that the code with functional programming is looping the array multiple time and wasting CPU cycles. But it the era of cloud computing power is cheap and easily accessible on demand. On the other hand, the complexity of code is directly related to its readability and cleanness and easier to alter.

Please share your view in the comments.