Educational institutions preparing students for software engineering careers require systematic approaches to monitor coding skill development and provide structured practice environments. Current solutions often lack integration between external platform tracking and institutional assessment needs, creating fragmented workflows for educators and students. This research presents LeetTrack, an institutional framework designed to automate coding progress monitoring while providing an integrated practice environment with real-time code execution capabilities. The system architecture employs a dual-panel approach separating administrative functions from student interactions, enabling educators to create custom problem banks, organize student batches, and analyze department-level performance metrics. Students access personalized dashboards displaying difficulty-categorized statistics, solve institution-assigned problems through an embedded code editor, and view comparative rankings based on administrator-defined assessments. The framework retrieves publicly available coding profile metadata through scheduled synchronization processes, maintaining current progress information without manual intervention. A sandboxed execution engine processes student submissions across multiple programming languages, applying resource constraints and providing immediate feedback on solution correctness. Token-based comparison algorithms evaluate outputs following competitive programming conventions, reducing false rejection rates caused by formatting variations. Implementation utilizes modern web technologies including component-based frontend architecture, RESTful backend services, and relational database management with type-safe query operations. Evaluation demonstrates the system effectively consolidates coding analytics, practice functionality, and administrative controls into a unified platform suitable for institutional deployment in placement preparation contexts.

The This research presented LeetTrack, an institutional framework for automated coding progress monitoring with integrated practice environment. The system addresses fragmentation between external coding platforms and institutional assessment needs by consolidating essential functionality into a unified web application. The framework architecture separates administrative and student interfaces while maintaining consistent data representation across all interactions. Administrators create custom problem banks with hidden test cases, organize students into performance-based batches, and access department-level analytics dashboards. Students view personalized progress statistics, solve assigned problems through an embedded code editor supporting multiple programming languages, and compare performance against institutional peers through real-time leaderboards. Implementation employed modern web technologies including component-based frontend architecture, RESTful backend services, and relational database management with type-safe query operations. Token-based authentication enables deployment in restricted environments where cookie- based sessions face limitations. Sandboxed code execution through external service integration ensures security without requiring institutional infrastructure for isolation. Evaluation demonstrated successful functional validation across all primary capabilities including authentication, code execution, submission recording, and ranking computation. Performance measurements confirmed acceptable response times for interactive use. Security testing verified protection against common attack vectors including authentication bypass, role escalation, and injection attacks. The primary limitation of the current implementation is dependence on external execution services for code processing. Future work could explore self-hosted execution infrastructure for institutions requiring complete data isolation. Additional enhancements under consideration include plagiarism detection for identifying copied submissions, live contest functionality for timed competitive events, and discussion forums enabling peer learning around specific problems. The LeetTrack framework provides a practical solution for educational institutions seeking to improve coding skill development outcomes through systematic progress monitoring and structured practice environments. By reducing administrative burden while improving visibility into student progress, the system enables more effective placement preparation programs aligned with industry expectations.

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