Past Projects

I developed a Pointing Poker backend and frontend web application (GitHub Page) that works well enough for an internal team to use. It requires nodejs on the backend. The front end was built with React.

I built it because I was frustrated with the performance and reliability of public servers, and because I wanted to learn more how to use React beyond a trivial tutorial. It’s based on websockets, and all data is immediately replicated between all clients. There’s no code to reconnect if the websocket fails or if websockets don’t work, but it’s worked without a single flaw within an internal network, which is how I’ve used it.

Thanks to Mischa Berlin for a submission allowing random name generation!

The Lunchbus is a project I made to play with Spring Boot + websockets + AngularJS 1.5 + Groovy + Redis. This may be interesting to those who are interested to see how these are set up. At the time I ran it on Heroku – although due to the age I suspect the deployment configuration is no longer valid.

The lunchbus app keeps track of who owes lunches and to whom, a list of people and places that can be selected, a button to randomly select a place, a chat functionality, and a demonstration of high-speed log output from backend. Persistence is provided by Redis. Due to how it uses Redis, it’s just almost ready for horizontal scaling with multiple servers, for that time that you have over 100,000 people going to lunch with you. All that’s needed for that is to integrate Spring Boot to Redis pubsub.

JavaFX Utilities - Zoom and Pan Charts and Pane Scaling for JDK 7+ (no longer maintained).

Final project for my master of science in Computer Science at Rochester Institute of Technology.

Embedded sensor monitoring systems deal with large amounts of live time-sequenced stream data. The embedded system requires a lower overhead data store that can work with limited resources and be able to run reliably and unattended even in the face of power faults.

Relational database management systems (RDBMS) are a well-understood and powerful solution capable of storing time-sequenced data; however, many have a high overhead, are not sufficiently reliable and maintenance free, or are unable to maintain a hard size limit without adding substantial complexity.

RealDB is a specialized solution that capitalizes on the unique attributes of the data stream storage problem to maintain maximum reliability in an unstable environment while significantly reducing overhead from indexing, space allocation, and inter-process communication when compared to a traditional RDBMS-based solution.