I am a second-year Computer Engineering student at Dwarkadas J. Sanghvi College of Engineering (DJSCE), Mumbai (Class of 2029). I am passionate about AI, systems programming, and full-stack web development. I enjoy writing clean, optimized code and contributing to open-source software.
- 🎓 Pursuing a B.Tech in Computer Engineering at DJSCE (Expected 2029).
- ⚙️ Interested in Systems Programming, Artificial Intelligence, Robotics, and Data Structures.
- 🚀 Contributor to TheAlgorithms/Java.
- 📬 Reach out to me at: vmprajapati@zohomail.in.
💻 Languages
|
🌐 Web Technologies
|
|
🧠 Key Concepts 🎓 Data Structures & Algorithms (DSA) 🧩 Object-Oriented Programming (OOP) 💾 Memory Management & Pointers |
🔧 Tools & IDEs
|
🚀 TheAlgorthms/Java — Open Source Contribution
- Merged 10 pull requests into TheAlgorithms/Java (66k+ stars), one of the largest open-source algorithm repositories on GitHub.
- Implemented algorithms spanning ML, mathematics, sorting, and string processing: Naive Bayes Classifier, Linear Regression, Library Sort, Title Case conversion, Longest Common Substring, Padovan Sequence, Jacobsthal Number, Perrin Number, and Soble Number.
- Followed strict contribution guidelines including code style, Javadoc documentation, and JUnit test coverage for every submission.
- Technologies: HTML5, CSS3, JavaScript, AJAX
- Built a fully responsive multi-page restaurant website modelled on a real-world client site.
- Designed a custom responsive navigation bar with active-state page highlighting.
- Utilized AJAX to load page content dynamically, avoiding full-page reloads and providing a seamless user experience.
- Built a Node.js CLI tool that analyzes Java (Maven/Gradle) repositories to identify high-value test coverage gaps by combining JaCoCo coverage data with Git churn frequency, using the formula: (1 − line coverage) × ln(1 + commit count).
- Implemented a full 7-stage pipeline: repo intake, build detection, JaCoCo report generation, coverage parsing, git churn analysis, gap ranking, and automatic JUnit 5 test stub generation — with graceful fallback to static heuristics when builds fail.
- Covered by a 68-test suite; never modifies the user's real build files — all JaCoCo injection is done on a disposable workspace copy.
