Julia coding tests

Hiring Julia developers? You’ll want to make sure they can write reliable code and handle data science, machine learning, or scientific computing projects that make the most of Julia’s speed and precision.

With TestGorilla’s 12 universal coding tests, you can assess skills across 20 programming languages, including Julia.

These tests are a great way to find Julia programmers who can handle complex numerical problems, develop efficient algorithms, and deliver creative solutions for your data-heavy projects.

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What is a Julia skills test?

Julia is a powerful programming language designed for demanding numerical and scientific computing tasks. The combination of speed, flexibility, and precision makes it a top choice for developers working on data science, machine learning, and complex mathematical projects.

Julia coding tests, created by experts in software engineering and data science, focus on key skills like working with numerical methods, handling data structures, and improving computation speed and memory efficiency.

They assess technical skills and how well candidates understand Julia’s standout features, like multiple dispatch, parallel computing, and its standard library. Plus, these online tests emphasize problem-solving and critical thinking abilities, giving you a well-rounded view of each candidate.

Why use Julia skills tests?

Screen for essential Julia skills and key concepts like multiple dispatch, parallel computing, numerical methods, and data structures.
See how candidates tackle real-world challenges like optimizing complex calculations, processing massive datasets, or building fast machine learning models.
Find candidates who can write clean, scalable code and evaluate how well they structure their solutions, avoid bottlenecks, and make their code easy to maintain.
Go beyond syntax and make sure candidates can do more than write Julia code. These tests show their problem-solving process, debugging approach, and how they structure their solutions.

What roles can you hire for with a Julia coding test?

Software engineer

Software engineers need strong skills in high-performance computing, numerical analysis, and algorithm development to work with data-intensive applications. These tests help you find candidates who can write optimized, scalable Julia code.

Back-end developer

Julia’s speed and parallel computing capabilities make it useful for back-end systems that process large-scale computations, such as AI models or scientific simulations. The tests ensure candidates can handle API development, database interactions, and performance-heavy tasks.

Web developer

While Julia isn’t a go-to for web development, it’s useful in specialized cases where complex computations must be embedded in web applications. The Julia online tests assess a developer’s ability to integrate Julia with web frameworks and data pipelines.

Entry-level developer

If you're hiring junior developers new to Julia, testing evaluates their understanding of programming fundamentals, array manipulation, and ability to solve moderately complex coding problems.

12 programming skills tested in Julia and 19 other coding languages

Evaluate 12 essential programming skills with coding challenges and simulated tasks. Let candidates solve problems using Julia or any of 19 additional programming languages based on their expertise and experience.

Coding: Data Structures - Stacks and Queues

This intermediate-level coding challenge assesses candidates' proficiency in manipulating stacks and queues. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Debugging

This intermediate-level coding challenge focuses on candidates’ ability to interpret and debug code, based on a set of requirements, in the programming language of their choice. You can configure which programming languages will be available.

35 min

Details

Coding: Entry-Level Algorithms

This coding test assesses candidates' ability to program a basic algorithm, in the programming language of their choice. You can configure which programming languages will be available for your candidates to choose from.

15 min

Details

Coding: Intermediate-Level Algorithms

This coding test assesses candidates' intermediate-level programming skills, in the programming language of their choice. You can configure which programming languages will be available for your candidates to choose from.

35 min

Details

Coding: Data Structures - Heaps

This intermediate-level coding challenge assesses candidates' proficiency in working with heaps, in the programming language of their choice. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Data Structures - Graphs

This intermediate-level coding challenge assesses candidates' proficiency in graph data structures. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Data Structures - Binary Search Trees

This intermediate-level coding challenge assesses candidates' proficiency in working with binary search trees, in the programming language of their choice. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Data Structures – Binary Trees

This intermediate-level, language-agnostic coding challenge assesses candidates' proficiency in manipulating binary trees, enabling candidates to choose their preferred programming language. Employers can configure supported languages as needed.

35 min

Details

Coding: Data Structures – Linked Lists

This intermediate-level coding test evaluates candidates' ability to manipulate linked lists, in the programming language of their choice. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Data Structures - Arrays

This intermediate-level coding test evaluates candidates' ability to manipulate arrays, crucial for code optimization, in the programming language of their choice. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Data Structures – Strings

This intermediate-level coding challenge assesses candidates' proficiency in manipulating strings. You can configure which programming languages will be available for your candidates.

35 min

Details

Coding: Data Structures - Hash Tables

This intermediate-level coding challenge assesses candidates' proficiency in working with hash tables, in the programming language of their choice. You can configure which programming languages will be available for your candidates.

35 min

Details

Designed by Julia experts

TestGorilla’s Julia coding tests are designed by experienced developers with a broad range of programming skills. Every test goes through peer reviews, real-world calibration with feedback from hundreds of candidates, and regular updates to stay relevant so you get an accurate measure of a developer’s capabilities.

Tarpinder is a software developer with 10+ years of experience in PHP and MySQL, specializing in large-scale projects and complex database queries. He’s skilled in API integration and SQL for Oracle, including DDL, DML, and DCL statements. Outside of coding, he creates content and courses to share his expertise.

image of the subject-matter expert for this test

Ian is a software developer and functional programming enthusiast who builds data-heavy systems with Scala. He’s passionate about data engineering, machine learning, and open-source contributions. As the founder of a startup, he’s developing tech to decentralize royalty payments for Kenyan artists, blending his technical skills with a mission to support creatives.

Kiera is a full-stack developer with more than six years of experience coding at large tech companies. She’s fluent in JavaScript and TypeScript and has a tech stack that includes Angular, React, and Ionic. Through her diverse projects, she’s always exploring new frameworks and tools.

Dominic is a Ruby developer with 8+ years of experience building commercial applications. With a computer science background, he’s tackled projects of all sizes. He thrives on the challenge of programming, constantly refining his skills and solving unique problems.

Built-in features to support your Julia assessment

Want to maximize your chances of hiring the best Julia developer for the role? We recommend multi-measure testing.

By pairing your coding test with other relevant tests that evaluate your candidates' soft skills, cognitive abilities, knowledge, and preferences you can ensure you shortlist talent that's ready to contribute from day one.

Our in-depth Julia coding report offers insights into the approach each candidate took to arrive at their answers. The report includes:

🔹 Percentile-based scoring of candidates based on overall correctness (whether given inputs produce the correct output)

🔹 A timeline showing how candidates arrived at their answer, with specific actions such as copy/pastes highlighted for easy reference

🔹 A dynamic solution window, showing the candidates' final code coming together over time

🔹 Candidates' responses and results for each test case as well as the final validation use case

See what it looks like in action

All tasks and scenarios are solved in this integrated development environment (IDE). Once the candidate assesses the problem, they can choose Julia as their preferred language from the drop-down menu and solve the question.

Get started with your Julia coding test

Ready to start testing for Julia skills? Screen developers in three easy steps.

1. Create your assessment

Choose an existing universal coding test or create your own custom challenge. Select from up to 20 languages to include in your test including Julia, Python, and R.

2. Invite candidates your way

Connect with candidates by sending email invites directly from TestGorilla, straight from your ATS, or by sharing a direct link.

Illustration representing employees liking skills-based hiring

3. Analyze and shortlist top coders

Evaluate candidates’ Julia and coding skills, plus soft skills. Use our dashboard and reports to identify top performers.

Julia coding tests FAQ

A skilled Julia developer should have a strong understanding of numerical computing, multiple dispatch, parallel computing, and Julia’s standard library. Candidates for data science or machine learning roles should also be comfortable manipulating large datasets, optimizing algorithms, and integrating Julia with frameworks like Flux or JuMP. Problem-solving, adaptability, and strong analytical thinking are equally important.

Creating a custom coding assessment on TestGorilla is straightforward. Select Julia from the programming options, then write a brief test description, outline a coding problem, and define expected inputs and outputs. Set up test cases to evaluate the efficiency and accuracy of candidates’ solutions. You can also allow candidates to solve the problem in other programming languages to see how their skills translate across platforms.

Review the candidate’s overall score, which reflects the number of validation cases they passed. Then, use the view report section to watch their coding process in action, step by step. It shows how they wrote their Julia code and highlights copied or pasted sections. Lastly, check test cases to see how the candidate approached debugging and problem-solving and confirm that their final solution met all requirements.

To interview Julia developers, use a structured interview process with standardized questions to keep things fair and consistent. Focus on meaningful questions that evaluate candidates’ technical skills and practical experience with Julia. For example, you might ask, “How do you leverage multiple dispatch to improve code performance?” or “Can you describe how you’ve optimized algorithms for large-scale numerical computations using Julia?”

A skilled Julia developer should have a strong understanding of numerical computing, multiple dispatch, parallel computing, and Julia’s standard library. Candidates for data science or machine learning roles should also be comfortable manipulating large datasets, optimizing algorithms, and integrating Julia with frameworks like Flux or JuMP. Problem-solving, adaptability, and strong analytical thinking are equally important.

Review the candidate’s overall score, which reflects the number of validation cases they passed. Then, use the view report section to watch their coding process in action, step by step. It shows how they wrote their Julia code and highlights copied or pasted sections. Lastly, check test cases to see how the candidate approached debugging and problem-solving and confirm that their final solution met all requirements.

Creating a custom coding assessment on TestGorilla is straightforward. Select Julia from the programming options, then write a brief test description, outline a coding problem, and define expected inputs and outputs. Set up test cases to evaluate the efficiency and accuracy of candidates’ solutions. You can also allow candidates to solve the problem in other programming languages to see how their skills translate across platforms.

To interview Julia developers, use a structured interview process with standardized questions to keep things fair and consistent. Focus on meaningful questions that evaluate candidates’ technical skills and practical experience with Julia. For example, you might ask, “How do you leverage multiple dispatch to improve code performance?” or “Can you describe how you’ve optimized algorithms for large-scale numerical computations using Julia?”