Hiring guide for FP Engineers

FP Developer Hiring Guide

The FP (Functional Programming) computer software programming language was developed by John Backus, a renowned computer scientist, in the late 1970s. It was introduced in his Turing Award lecture as an alternative to the prevailing imperative programming paradigm. FP is a high-level, declarative language that emphasizes mathematical functions and avoids changing-state and mutable data. Its design philosophy has significantly influenced modern functional languages like Haskell and Erlang. The details of its development can be found in Backus's original paper "Can Programming Be Liberated from the von Neumann Style?" published in 1978.

Ask the right questions secure the right FP talent among an increasingly shrinking pool of talent.

First 20 minutes

General FP app knowledge and experience

The first 20 minutes of the interview should seek to understand the candidate's general background in FP application development, including their experience with various programming languages, databases, and their approach to designing scalable and maintainable systems.

How would you explain functional programming?
Functional programming is a programming paradigm where programs are constructed by applying and composing functions. It is a declarative type of programming style that focuses on what to solve rather than how to solve (procedural programming). Its main features include pure functions, recursion, and avoidance of shared state, mutable data, and side-effects.
What are pure functions in functional programming?
Pure functions are a fundamental part of functional programming. A function is considered pure if it always produces the same output for the same set of inputs and it does not have any observable side effects such as network requests, data mutation, or console logs.
Describe the difference between imperative and functional programming.
Imperative programming is about writing code that describes in detail the steps that the computer must take to accomplish the goal. This is done by changing the program state through assignment statements. On the other hand, functional programming is about writing code that describes what it should accomplish without prescribing how to achieve it. It avoids changing-state and mutable data.
How would you handle side effects in functional programming?
In functional programming, side effects are handled by isolating them from the rest of the code. This can be done by using monads, which are a kind of container that can handle side effects in a controlled manner.
What are higher-order functions in functional programming?
Higher-order functions are functions that take other functions as arguments, return a function as a result, or both. They are a key part of functional programming and they provide a powerful abstraction mechanism.
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What you’re looking for early on

Has the candidate demonstrated a solid understanding of functional programming principles?
Can the candidate effectively communicate complex ideas?
Does the candidate show a good grasp of problem-solving skills?
Have they shown experience with the specific functional programming language(s) your company uses?

Next 20 minutes

Specific FP development questions

The next 20 minutes of the interview should focus on the candidate's expertise with specific backend frameworks, their understanding of RESTful APIs, and their experience in handling data storage and retrieval efficiently.

How would you use recursion in functional programming?
Recursion is a technique where a function calls itself as a subroutine. This can be used as a substitute for iterative control structures. In functional programming, recursion is often used to iterate over data structures, compute factorials, generate Fibonacci series, etc.
What are the benefits of immutability in functional programming?
Immutability in functional programming brings several benefits. It makes the code safer and easier to reason about since data cannot change once it's created. This eliminates a whole class of bugs related to data changes. It also makes it easier to implement undo/redo functionality, to parallelize code, and to compare data by reference instead of by value.
Describe the difference between map, filter, and reduce functions.
Map, filter, and reduce are higher-order functions that operate on arrays. Map applies a given function to each item of an array and returns a new array with the results. Filter creates a new array with all elements that pass a test implemented by the provided function. Reduce applies a function against an accumulator and each element in the array (from left to right) to reduce it to a single output value.
How would you handle errors in functional programming?
In functional programming, errors are often handled by returning a special type that represents either a successful result or an error. This could be an 'Either' type, with 'Left' representing an error and 'Right' representing a success, or a 'Maybe' type, with 'Just' representing a value and 'Nothing' representing an absence of a value.
What are the disadvantages of functional programming?
Functional programming has a steep learning curve, especially for developers coming from an imperative background. It can also lead to performance issues due to things like recursion and immutability. Debugging can also be more difficult in functional programming because control flow is not as explicit as in imperative programming.
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The ideal back-end app developer

What you’re looking to see on the FP engineer at this point.

At this point, a skilled FP engineer should demonstrate strong problem-solving abilities, proficiency in FP programming language, and knowledge of software development methodologies. Red flags include lack of hands-on experience, inability to articulate complex concepts, or unfamiliarity with standard coding practices.

Digging deeper

Code questions

These will help you see the candidate's real-world development capabilities with FP.

What does the following code do?
val list = List(1, 2, 3, 4, 5)
val result = list.map(_ * 2)
This code multiplies each element in the list by 2, creating a new list with the results.
What will be the output of the following code?
val list = List(1, 2, 3, 4, 5)
val result = list.foldLeft(0)(_ + _)
The output will be the sum of all elements in the list, which is 15.
What does the following code do?
val list = List(1, 2, 3, 4, 5)
val result = list.filter(_ % 2 == 0)
This code filters the list to only include even numbers, creating a new list with the results.
What will be the output of the following code?
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global

val future = Future { Thread.sleep(1000); 42 }
future.onComplete { case Success(value) => println(value) case Failure(exception) => println(exception) }
The output will be '42' printed to the console after a delay of 1 second.

Wrap-up questions

Final candidate for FP Developer role questions

The final few questions should evaluate the candidate's teamwork, communication, and problem-solving skills. Additionally, assess their knowledge of microservices architecture, serverless computing, and how they handle FP application deployments. Inquire about their experience in handling system failures and their approach to debugging and troubleshooting.

How would you optimize a recursive function in functional programming?
Recursive functions can be optimized in functional programming using techniques like tail recursion, where the recursive call is the final operation in the function. This allows the compiler or interpreter to optimize the recursion away and turn it into a loop, which can significantly improve performance.
What is currying in functional programming?
Currying is a technique in functional programming where a function with multiple arguments is transformed into a sequence of functions, each with a single argument. Curried functions are great to improve code reusability and functional composition.
Describe the difference between lazy and eager evaluation.
Eager evaluation is where expressions are evaluated as soon as they are bound to a variable. Lazy evaluation is where expressions are not evaluated until their results are needed. This can improve performance by avoiding unnecessary computations and creating potentially infinite data structures.

FP application related

Product Perfect's FP development capabilities

Beyond hiring for your FP engineering team, you may be in the market for additional help. Product Perfect provides seasoned expertise in FP projects, and can engage in multiple capacities.