This application is a fullstack web application which uses Next.js, FastAPI and PostgreSQL. This application was completed as part of the SWENG 894 Capstone Course in the Masters of Software Engineering program at Penn State. I worked with two other students to complete this product. This application features an authentication system, collaboration between users via sharing search workflows, and allows users to comments on a given article. We fostered a test driven development approach, and implemented automated test suites into our GitHub pipelines. This is a responsive application that will accommodate all screensizes, and can be deployed via docker. It consumes 3 external API's and has its own algorithm to determine an articles relevance based on the keywords provided by using the Natural Language Processing technique known as stemming.

This application converts PDF files into raw text using TesseractOCR, OpenCV, and tkinter for the GUI. The application parses 10 images at a time to avoid memory overflow on machines with limited memory. It has a progress bar and live updates on how many pages were processed. This application also includes some examples of shell scripting in Windows/Mac/Linux to assist with installing dependencies.

This application simulates maze environments, which are configurable in the ui/config.py file. You can set custom sizes, colors, starting point, goal point, etc. The player can also be moved with the W, A, S, D keys and manually destroy walls with the I, J, K, L keys. The application generates a traditional labyrinthian maze, and also a looping maze environment. The application then uses various algorithms such as Depth First Search, Breadth First Search and A* Search to solve the maze.

This app was made using Typescript and React. It uses the Deezer API to query your search results. It has a light and dark theme, and will also provide you short audio previews of the tracks.

This application was made using React and Firebase. It utilized Firebase authentication, Firebase database, and Firebase document storage. Users could add spots, add comments, and upload pictures. They could edit their posts, upload a profile picture and reset their password. A screen capture video of the website has been captured and is on youtube.

Bob's Skateshop was built using React, Bootstrap and Redux. Redux handles the state of the shopping cart. The data for the products is pulled from an array of objects stored in the application, and there is no backend at this time. There are no plans to implement a backend as then I would actually need to deliver on the ficticious goods.

This application attempts to convert PDF files into raw text using the crate pdf-extract. It uses Slint for the GUI. This application is much faster than the PythonOCR shown below. However, the pdf processing is much more simplistic and the result is closer to simply copying and pasting text from a pdf. As my knowledge of Rust continues to grow, I hope to revisit this for a more robust solution.