Inspiration
While preparing for coding interviews, I realized that solving DSA problems without tracking consistency or weak areas leads to random and unstructured practice. I wanted to build a system that makes my preparation measurable and goal oriented.
What it does
DSA Tracker lets users log problems by topic, difficulty, and platform, track daily streaks, and visualize progress. It highlights weak areas and helps turn inconsistent practice into a structured learning path.
How we built it
We designed a structured data model for problems, tags, and user progress. We implemented features for logging problems, filtering by categories, tracking streaks, and building analytics dashboards to visualize improvement over time.
Challenges we ran into
The main challenges were deciding meaningful metrics for progress, designing a simple yet useful UI, and ensuring streak tracking logic remained accurate and consistent.
Accomplishments that we're proud of
We built a fully functional system that mirrors real coding preparation workflows. The streak system and analytics dashboard helped transform raw practice data into actionable insights.
What we learned
We learned how to translate real-world learning habits into software features, design efficient data structures for tracking progress, and build user-focused analytics. It also reinforced the importance of consistency in skill development.
What's next for DSA Tracker
Next, we plan to add personalized problem recommendations, AI-based weak topic detection, and integration with coding platforms like LeetCode and Codeforces for automatic tracking.
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