Student Research Symposium Program Portal: Submission #113

Abstract APIs are crucial for modern application development, but discovering and accessing them efficiently remains difficult. This project introduces an automated API indexing and search platform designed to simplify that process. Using Python’s BeautifulSoup and Selenium libraries, the system scrapes public websites to extract key API information such as names, descriptions, and documentation links. The gathered data is organized into a searchable index, which powers a user-friendly web interface. Users can input keywords and receive quick, relevant API results—similar to using a traditional search engine. This approach helps developers find APIs faster and with greater accuracy. By combining static HTML parsing with dynamic web automation, the platform ensures broad and effective data collection. Early results show that this hybrid scraping method successfully builds a reliable API dataset. Planned improvements include adding ranking algorithms, collecting user feedback, and expanding data sources for wider coverage. This project demonstrates how web scraping and automation can address real-world problems in information retrieval, making API discovery more accessible and efficient for developers.