GitHub: coding-interview-university hits 343k
- John Washam’s GitHub repo “coding-interview-university” reached about 343,000 stars this week, resurfacing as a go-to roadmap for software-engineering interview prep. - The repo still pitches a months-long CS grind — 8 to 12 study hours a day in Washam’s case — and now sits among GitHub’s most-starred projects. - That matters because the market keeps rewarding classic interview patterns, even as hiring tools and day-to-day coding workflows shift toward AI.
A GitHub repository is back in the spotlight because it captures something awkward but true about software hiring: the interview game still looks a lot like it did years ago. John Washam’s “coding-interview-university” just crossed roughly 343,000 stars, which puts a self-study checklist for algorithms and computer-science basics in very rare company on GitHub. The repo is old by internet standards. But it keeps spreading because the underlying problem never really went away — companies changed tools, not the core shape of the technical screen. (github.com) ### What is this repo, exactly? It started as Washam’s personal study plan for getting hired as a software engineer at a large company. In the README, he says it began as a short to-do list and expanded into a giant curriculum covering data structures, algorithms, system basics, and coding practice. He also says he studied 8 to 12 hours a day for several months before landing an SDE role at Amazon. That ori(github.com)extbook and more like a map someone actually used. (github.com) ### Why does 343,000 stars matter? Because that is not normal scale for a study guide. GitHub’s own listing shows 343,000 stars and more than 82,000 forks, and star-history trackers place it among the platform’s most-starred repositories. In plain English, this is not a niche prep doc for anxious candidates on Reddit. It is one of the internet’s canonical software-interview artifacts. (([github.com)alking about it now? The immediate spark seems to be a fresh wave of social posts reducing interview prep to a compact list of recurring patterns — things like Two Sum, Merge Intervals, binary search variants, LRU cache design, and Dijkstra. That short-list style works well on social media because it feels actionable. But once people ask what to study beyond a handful of famous LeetCode (github.com)o. The short checklist is the hook. The repo is the full course. (github.com) ### So is this just a LeetCode list? Not really. That is the interesting part. The README is much broader than “solve 100 questions.” It walks through asymptotic analysis, arrays, linked lists, trees, heaps, graphs, recursion, dynamic programming, and more. Basically, it treats coding interviews as compressed computer-science exams, not just puzzle sessions. That matches how many candidates experience the p(github.com)tation that you understand why the standard tricks work. (github.com) ### Why hasn’t AI killed this style of prep? Because interviews are still trying to measure reasoning under constraints. AI can help people study, explain patterns faster, and even generate practice variants. But the hiring loop at many product companies still centers on whether a candidate can recognize a pattern, choose a data structure, and explain tradeoffs live. If that is the test, (github.com)The repo’s continued growth is basically evidence that the market still values those signals. (github.com) ### Is the repo still actively maintained? Not much in the usual sense. GitHub shows the latest visible commit on the main repo is from about two years ago. But that almost helps its reputation. The document feels “finished” rather than abandoned — a stable syllabus people can copy, fork, translate, and adapt without worrying that the ground will move every week. For a study plan, stability is a feature. (([github.com)### What does this say about hiring? It says community consensus is still strong around the basics. The exact companies, job titles, and prep tools change. The core interview canon does not change much. Arrays, hash maps, trees, graphs, dynamic programming — those are still the grammar of technical interviews, and “coding-interview-university” remains the internet’s biggest organized reminder of that. (git([github.com) Bottom line The repo hitting 343,000 stars is not just a vanity metric. It is a signal that, in 2026, software candidates still believe the surest path into big-company engineering runs through the same old CS gauntlet — just with better packaging and a lot more GitHub stars. (github.com)
