Hiring guide for Alice ML Engineers

Alice ML Developer Hiring Guide

Alice ML, or simply Alice, is a functional programming language that blends the enriched concepts of distributed computing, concurrent and constraint programming. It was designed to support advanced features such as higher-order modules and components. The language also supports lazy evaluation and futures for handling concurrency. Alice ML extends Standard ML with rich support for concurrent, distributed, and constraint programming in order to provide programmers with a high degree of expressiveness without sacrificing performance or safety.

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

First 20 minutes

General Alice ML app knowledge and experience

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

What are the main features of Alice ML?
Alice ML has several key features including lazy evaluation, higher-order functions, strong typing, system programming, modular programming, distributed programming, and persistence.
How would you describe the typing system in Alice ML?
Alice ML uses a strong, static typing system. This means that the type of a variable is known at compile time, which can help catch errors before the program is run.
What is the significance of higher-order functions in Alice ML?
Higher-order functions are functions that can take other functions as arguments and/or return functions as results. They are a fundamental part of functional programming and are heavily used in Alice ML to create more abstract and reusable code.
Describe the difference between eager and lazy evaluation in Alice ML.
Eager evaluation means that expressions are evaluated as soon as they are bound to a variable. Lazy evaluation, on the other hand, means that expressions are not evaluated until their results are actually needed. Alice ML supports both, but defaults to eager evaluation.
What are futures in Alice ML and how would you use them?
Futures in Alice ML are a way to handle computations that have not yet completed. They are essentially placeholders for the results of these computations. You would use futures in Alice ML to write concurrent programs, where different computations can be carried out in parallel.
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What you’re looking for early on

Does the candidate have a strong understanding of Alice ML?
Has the candidate demonstrated problem-solving skills?
Is the candidate able to communicate effectively?
Does the candidate have experience with machine learning algorithms?

Next 20 minutes

Specific Alice ML 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 handle exceptions in Alice ML?
Exceptions in Alice ML are handled using the raise and handle constructs. You would use raise to signal an exception, and handle to catch and deal with it.
What is the role of pickling in Alice ML?
Pickling in Alice ML is a way to serialize and deserialize data. This allows data to be saved to disk or sent over a network, and then later restored to its original form.
Describe the difference between system programming and distributed programming in Alice ML.
System programming in Alice ML refers to writing code that interacts directly with the operating system, such as file I/O or network communication. Distributed programming, on the other hand, refers to writing code that runs on multiple machines and communicates over a network.
How would you implement modular programming in Alice ML?
Modular programming in Alice ML is implemented using structures and functors. Structures are collections of related definitions, and functors are functions that operate on structures.
What is the role of constraints in Alice ML?
Constraints in Alice ML are a way to express relationships between variables that must hold for a program to be correct. They are used in constraint programming, a programming paradigm that Alice ML supports.
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The ideal back-end app developer

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

At this point, a skilled Alice ML engineer should demonstrate strong problem-solving abilities, proficiency in Alice ML 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 Alice ML.

What does this simple Alice ML code do?
val x = 10;
val y = 20;
val z = x + y;
This code declares two variables x and y with values 10 and 20 respectively. Then it declares another variable z and assigns it the sum of x and y. So, z will be 30.
What is the output of this Alice ML code snippet?
val s = "Alice ML";
val t = substring(s, 0, 5);
The code takes a substring of the string s starting from index 0 and ending at index 5 (exclusive). So the output will be 'Alice'.
What does this Alice ML code snippet do?
val l = [1, 2, 3, 4, 5];
val m = List.map (fn x => x * 2) l;
This code declares a list l of integers. It then applies the function 'fn x => x * 2' to each element of the list using the List.map function, resulting in a new list m where each element is twice its corresponding element in l. So, m will be [2, 4, 6, 8, 10].
What does this Alice ML code snippet do?
val r = Promise.new ();
val _ = Thread.fork (fn () => (Thread.delay (Time.seconds 1); Promise.keep r "Hello"));
val s = Promise.get r;
This code creates a new promise r, then forks a new thread that waits for 1 second and then fulfills the promise with the value 'Hello'. The main thread then immediately tries to get the value of the promise. Since the value is not yet available, it will block until the value is available.

Wrap-up questions

Final candidate for Alice ML 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 Alice ML application deployments. Inquire about their experience in handling system failures and their approach to debugging and troubleshooting.

How would you use pattern matching in Alice ML?
Pattern matching in Alice ML is used to destructure data and to control the flow of a program. It is a powerful feature that allows you to write more expressive and concise code.
What are the benefits and drawbacks of using Alice ML for a large-scale project?
Benefits of using Alice ML for a large-scale project include its strong typing system, which can prevent many errors, its support for various programming paradigms, and its powerful abstraction mechanisms. Drawbacks include its relatively small community and the lack of libraries compared to more popular languages.
How would you debug a complex issue in an Alice ML program?
Debugging a complex issue in an Alice ML program would involve using the Alice ML debugger, adding print statements to the code, and using the type system to help identify potential sources of the problem.

Alice ML application related

Product Perfect's Alice ML development capabilities

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