AlgoAtlas — One Focused Path Through the DSA Chaos
The problem isn't finding DSA questions. It's deciding what to solve next.
A friend of mine was preparing for coding interviews and kept running into the same problem: there were too many resources and no clear path through them.
LeetCode. Codeforces. NeetCode. Blind 75. Striver A2Z. GitHub repositories. Interview resources.
All useful. But constantly switching between them made practice feel more complicated than it needed to be.
So for the Hacktoberfest Weekend Challenge: Build for a Friend, I built AlgoAtlas — a focused DSA practice workspace designed to help learners decide what to practice next.
What I Built
AlgoAtlas brings problem discovery, practice planning, recommendations, progress tracking, and coding into one workspace.
It includes:
- A practice dashboard with solved problems, streaks, topics, and practice time
- Topic-based problem exploration
- Search and filters for topic, difficulty, source, and platform
- Curated collections including Blind 75 / Grind 75, NeetCode 150, and Striver A2Z
- A recommendation system that suggests the next problem based on practice history, topic coverage, popularity, and interview relevance
- A roadmap covering important DSA patterns
- A problem-specific coding workspace
- Local drafts and progress tracking
- Local execution for JavaScript, Python, Java, and C++
The goal is simple:
Spend less time deciding what to solve and more time actually solving.
Demo
🚀 Live Demo:
https://hacktoberfest-weekend-challenge-build-xnkg.onrender.com
Code
💻 GitHub Repository:
https://github.com/Swetha-Oruganti/Hacktoberfest-Weekend-Challenge--Build-for-a-friend-_AlgoAtlas
How I Built It
I intentionally kept the implementation small: the entire application is built with just two files — index.html and server.js.
The frontend uses HTML, CSS, and Vanilla JavaScript, with browser LocalStorage for local progress and preferences.
The Node.js backend provides the /api/run endpoint and handles local code execution. It creates temporary execution directories, runs the selected language through the appropriate runtime/compiler, captures the output, and removes the temporary files afterward.
AlgoAtlas currently supports:
JavaScript · Python 3 · Java · C++17
For problem-specific practice, the backend can also create language-specific sample-test harnesses around the user's solution.
The application does not submit solutions to LeetCode, Codeforces, CodeChef, or another online judge. The current implementation focuses on local execution and public sample checking.
Why Does Open Innovation Matter?
DSA preparation already has a huge open ecosystem.
There are problem collections, interview-preparation resources, contest archives, roadmaps, GitHub repositories, and community resources spread across different platforms.
I didn't want to rebuild all of that.
I wanted to connect it in a way that makes it easier to navigate.
AlgoAtlas keeps the original source links visible instead of hiding where problems came from. It brings resources such as Blind 75 / Grind 75, NeetCode 150, Striver A2Z, Codeforces, CodeChef, GeeksforGeeks, and community resources into one practice experience.
That is what open innovation means to me here:
Build on the ecosystem that already exists, connect it thoughtfully, and make it more useful for the person using it.
My Agent Session
My Slug-
I want to build AlgoAtlas: a practice platform that connects coding problem sources, recommends a user-selected number of distinct problems based on topic coverage, popularity, and recent company interview reports, and includes authentication and an IDE.
Planning focused on a single workspace for curated multi-platform practice, a problem-count preference, progress tracking, and an integrated editor.
The editor should not be tied to one question. It needs useful language templates, indentation on Enter, and working Tab indentation.
The editor was adjusted toward generic language starters and automatic indentation. The problem-specific Two Sum starter remains appropriate only when solving that specific problem.
Recommendations should prioritize broad topic and pattern coverage, number of attempts, and recent FAANG or popular-company interview reports. Include NeetCode 150, Blind 75, GeeksforGeeks, takeUforward, CodeChef, Codeforces, Reddit reports, and useful repository collections. Avoid duplicate questions while preserving novel patterns.
The curated catalog uses problem metadata and source collections to support pattern coverage and reduce duplicates. Recommendation metadata can show attempt volume and recent reports when that data is available.
For all languages, keep generated comments on one line. Problems without imported examples should not fail with a missing-samples compiler error. I also want the app to submit solutions instead of sending users to another site.
Shortened generated TODO comments, disabled editor soft wrapping, and added a compile-only fallback when there are no imported sample cases. This confirms syntax but cannot compare expected outputs without a problem-specific test contract. Submission remains unavailable without a supported authenticated judge integration.
If you cannot scrape every problem, show the link to that problem for each entry.
Added a publisher link beside every problem in Explore and an Open publisher problem link in the IDE. Problems with alternate source entries also show those links in the details.
I used DevRelay as an agent-assisted development workflow while building AlgoAtlas.
My workflow was:
Idea → Planning → Implementation → Debugging → Testing → Refinement
DevRelay helped me work through development tasks and iterations while I remained responsible for the product decisions, implementation, and final integration.
The current AlgoAtlas implementation itself does not contain an AI model or external AI API. The recommendation system is application logic based on practice history, topic coverage, popularity, and interview relevance.
I chose to keep that distinction clear rather than adding an AI API simply for the sake of calling the project AI-powered.
Prize Categories
Hacktoberfest Weekend Challenge — Build for a Friend
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