Research Symposium Program - Individual Details
5th annual Undergraduate Research Symposium, April 17, 2025
Matthew Brady He/Him C -3 R- 5
BIO
Hello All! My name is Matthew Brady and I am a computer Science Major from Stuart, Florida. Some of my hobbies include skateboarding, soccer, Video games, and playing guitar! While studying at Florida State University, my academic focus has centered around user interface and user experience (UI/UX) design, particularly through front-end technologies such as JavaScript, CSS, and HTML. I’ve also developed a strong interest in Python for web scraping and automation, using tools like BeautifulSoup and Selenium to extract and organize data from dynamic web environments. Additionally, I enjoy exploring C++ through game design projects, where I apply core programming concepts to interactive applications. My coursework and personal projects have further deepened my understanding of data structures, algorithms, and object-oriented programming, forming a strong foundation for software development across a variety of domains.
Scrape and Search: Your API Web Finder
Authors: Matthew Brady, Karen WorksStudent Major: Computer Science
Mentor: Karen Works
Mentor's Department: Computer Science Mentor's College: N/A Co-Presenters:
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.
Keywords: Web Scraping, API, Indexing