Algorithm Write-Ups That Show You the Moves, Not Just the Code
You've read the KMP explanation that starts with a wall of index arithmetic and ends with you nodding along without actually understanding anything. The next-match table appears, the code compiles, and you move on—still not quite sure why it works. What if someone just drew it out for you, frame by frame? That's the idea behind algorithm-base, a repository of algorithm write-ups built around animated diagrams.
What It Does
algorithm-base is a collection of explanatory articles covering data structures and classic algorithms, with a heavy emphasis on visual and animated walkthroughs. The README organizes the material into clear sections: foundational data structures (hash tables, stacks and queues, linked lists, recursion, trees), string matching algorithms (BF, BM, and KMP), and sorting algorithms (bubble sort, simple selection sort, insertion sort, shell sort, merge sort, and more). Each entry links to a dedicated write-up in the repository.
The write-ups are labeled by format in the README itself—some are marked as animated simulations, others as drawn-out explanations or descriptions. That labeling is a useful signal: the material on hash tables is billed as a long-form animated deep dive, while the recursion piece is described as a drawing-based description. The project also points readers to an online reading site for a more stable experience, and the repository is maintained by the author behind the Chinese-language account 程序厨.
Why It's Cool
The animations are the whole point. Most algorithm resources treat visualization as a nice-to-have—a single GIF at the top of an otherwise text-heavy post. Here, the visual explanation appears to be the primary teaching mechanism, which matters a lot for algorithms like KMP where the failure function is genuinely hard to hold in your head as static text.
The curriculum has a sensible spine. Rather than dumping a pile of LeetCode solutions, the README lays out prerequisites first—hash tables, stacks, queues, linked lists, recursion, trees—before moving into string matching and sorting. If you're shaky on the fundamentals, you know exactly where to start.
It covers the algorithms people actually stumble over. KMP and BM are the classic string-matching algorithms that trip up interview candidates. Getting a dedicated animated treatment of each, alongside the brute-force BF baseline for comparison, is a practical progression.
It's an active, community-oriented project. The README explicitly invites code contributions (you can add the maintainer on WeChat with a note about contributing), thanks contributors by name, and mentions a study group for interview prep that's free and ad-free. The author also states the repository will keep being maintained.
One honest caveat: the README and the linked material are written in Chinese. If you don't read Chinese, the animated diagrams may still carry some of the load, but the surrounding explanation won't. That's worth knowing before you dive in.
How to Try It
- Start with the repository: github.com/chefyuan/algorithm-base.
- For the most stable reading experience, the README recommends the online site at www.chengxuchu.com.
- Pick your entry point based on where you're stuck. If data structures are the gap, begin with the hash table deep dive. If you're prepping for interviews, jump straight to the KMP write-up and work backward through BF and BM.
- There's nothing to install—these are articles, not a library. Open a link and read.
- If you want to contribute write-ups or fixes, the README lists the maintainer's WeChat contact for contributors.
Final Thoughts
algorithm-base isn't a framework or a tool you'll add to a project—it's a study resource, and it's best suited to developers who learn visually and are working through data structures and interview-style algorithms. The animated-diagram approach is genuinely useful for the trickier material, and the organized structure means you can target exactly the topic you're weak on. The language barrier is real for non-Chinese readers, but if that's not an obstacle for you, this is a solid place to finally understand why KMP doesn't backtrack.
Follow @githubprojects for more developer tools and open source projects.