Chesstify: Chess Game Database Management System using Portable Game Notation

Abstract

This study presents Chesstify, a web-based chess game database management system designed to support efficient storage, retrieval, visualization, and analysis of chess games using Portable Game Notation (PGN). We propose a unified approach that integrates data management, interactive visualization, and engine-based analysis within a single platform. The system applies a structured database schema to store game metadata and move sequences, while Forsyth–Edwards Notation (FEN) is used dynamically to represent board positions for real-time interaction and evaluation. The Stockfish engine is integrated to provide position evaluation and best-move recommendations, enabling deeper analytical insights. Our study shows that the system performs reliably across all core functionalities, including PGN upload and parsing, search and filtering, board visualization, move validation, and advanced analysis features. Black-box testing results show a 100% success rate, confirming that the system meets all functional requirements and handles both valid and invalid inputs correctly. The findings demonstrate that the proposed system ensures data consistency, efficient query performance, and stable operation in managing large collections of chess games. This study can contribute to the development of data-driven chess applications by providing a scalable and extensible framework for chess data management and analysis. The proposed system not only supports practical use for players and analysts but also offers potential integration with machine learning and data mining techniques for future research. The results highlight the effectiveness of combining standardized notation, database systems, and analytical engines to enhance the usability and functionality of modern chess platforms.