Is Awesome Interviews still updated in 2024?

No, the README indicates it's no longer actively supported, so resources may be stale; always cross-check links with current trends.

How to find React interview questions in Awesome Interviews?

Scroll to the ReactJS section under Programming Languages for curated links, but supplement with recent frameworks like Next.js for comprehensive prep.

Awesome Interviews or LeetCode: which is better for coding practice?

Awesome Interviews aggregates lists including exercises, but LeetCode offers interactive problems; use Awesome for breadth and LeetCode for hands-on practice.

What are the best algorithm resources listed here?

Check the Algorithms section for common questions, but verify solutions since links might point to outdated blogs or sites.

How to contribute a new interview resource to Awesome Interviews?

Follow the contribution guidelines in the README, though the project is inactive, so pull requests may not be reviewed promptly.

Does it cover system design questions for senior roles?

Yes, under Design Patterns or Comprehensive Lists, but resources might lack depth compared to dedicated books or courses.

Awesome interview questions

A curated collection of technical interview question lists across programming languages, frameworks, databases, and CS topics.

Visit Website GitHub

What is Awesome interview questions?

Awesome Interviews is a curated GitHub repository that serves as a meta-list of technical interview question collections. It organizes links to interview resources—questions, answers, coding exercises, and guides—across hundreds of technologies and computer science topics, helping developers prepare for job interviews systematically.

Target Audience

Software developers, engineers, and computer science students preparing for technical interviews at tech companies, especially those seeking structured study materials across multiple tech stacks.

Value Proposition

It saves time by aggregating scattered interview resources into a single, well-organized repository, covering both niche and mainstream technologies with community-vetted links, all under an open-source, contribution-friendly model.

Overview

:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:

Use Cases

Best For

Finding interview questions for a specific programming language like Python or JavaScript

Related Projects

Community-curated · Updated weekly · 100% open source

Found a gem we're missing?

Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.

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Studying algorithm and data structure problems before coding interviews

Preparing for framework-specific interviews (e.g., React, Angular, Django)

Exploring system design and DevOps interview questions

Practicing database and SQL interview scenarios

Getting curated lists of questions for senior-level positions

Not Ideal For

Developers needing interactive coding practice with real-time feedback
Teams requiring guaranteed up-to-date questions for fast-moving tech stacks
Individuals seeking personalized, adaptive study plans or mock interview simulations
Projects that depend on integrated progress tracking or assessment tools

Pros & Cons

Pros

Extensive Categorization

The README shows over 50 categories, from Android to Data Science, organizing questions by technology and CS domains for efficient browsing.

Community-Driven Resources

It encourages contributions via open-source guidelines, allowing crowdsourced updates to interview materials across many niches.

Multi-Level Content Depth

Includes resources for beginners to senior developers, with coding exercises and guides, as noted in the Key Features.

Broad Tech Coverage

Spans frontend, backend, DevOps, and more, evidenced by sections like Blockchain, Security, and Data Science in the table of contents.

Cons

Inactive Maintenance

The README explicitly states 'This project is no longer actively supported,' risking outdated or broken links.

Unverified Link Quality

As a meta-list, it aggregates external sources without curation for accuracy or relevance, leading to variable resource quality.

No Integrated Practice Tools

Lacks interactive features like code editors or mock interviews found on dedicated platforms, limiting hands-on preparation.

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