Software Engineering Commons^™

Tavern Table: A Peer-To-Peer Online Platform For Collaborative Dungeons & Dragons Campaigns, Dustin Needham, Kristen Avery, Aidan Martin, Seth Poindexter

ATU Scholars Symposium

Designed to address the lack of free, accessible, and feature-complete online Dungeons & Dragons gameplay platforms, Tavern Table gives users the ability to create or participate in Dungeons & Dragons campaigns online via peer-to-peer multiplayer. This platform is targeted primarily for two sets of users: Dungeon Masters (the game masters), who will be creating and hosting campaigns for players to participate in, and the players participating in said campaigns. We chose the Unity Real-Time Development Platform to develop Tavern Table as it was a free and effective platform that supported 2D game development as well as peer-to-peer multiplayer. To create …

Simple D&D: A Web-Based Character Creation System For Dungeons & Dragons, Brennan M. Bondio, Dalton N. Tate, Landon F. Boyd

ATU Scholars Symposium

Dungeons & Dragons, published by Wizards of the Coast, is a widely played tabletop role-playing game that requires players to create detailed characters governed by structured rule systems. Character creation involves managing interdependent attributes, calculations, and constraints that can be difficult for new players and time-consuming even for experienced participants. These complexities create a barrier to entry and reduce efficiency during gameplay preparation.

This project addresses that challenge through the development of Simple D&D, a web-based character creation system designed to streamline and automate rule-driven character configuration. The system aims to reduce manual calculation errors and setup time while maintaining …

Digitizing Transportation Operations At Safe Haven, Luke S. Garrett, William B. Turk, Clay A. Curtis, Aiden H. Behler

ATU Scholars Symposium

Safe Haven’s transportation department currently relies on a paper-based documentation process that requires physical transfer of records between buildings and repeated manual uploading of documents into storage systems. This workflow creates delays, redundant administrative tasks, and increased risk of misplaced or inconsistent records. Drivers, transportation coordinators, reviewers, and clients all interact with this process, making efficiency and data accuracy critical to daily operations.

This project develops a web-based transportation scheduling system designed to digitize documentation workflows and automate many of the repetitive tasks. The system replaces physical records with digital data management, reducing unnecessary manual handling and improving information accessibility …

Moneyup: A Predictive Financial Management System For College Students, Isaiah J. Adams, Malaya E. Wilburd, Dan V. Le, Joshua P. Golden

ATU Scholars Symposium

College students often lack accessible tools that combine real-time financial tracking, mobile accessibility, predictive analytics, and secure system design, leaving many without structured insight into their spending behavior. MoneyUP is a full-stack financial management platform developed to address these challenges through a secure, data-driven budgeting system deployed as both a web application and a cross-platform Flutter mobile application. The system integrates the Plaid API in its Sandbox environment to synchronize simulated banking data for secure testing without exposing live financial credentials. Transaction data is processed and stored using Supabase with a relational PostgreSQL database structured to enforce normalization, referential integrity, …

Llm-Based Stock Sentiment And Market Intelligence Platform, Joshua Thrower, Andrew Pinkerton, Ian Duggan, Wyatt Lester

ATU Scholars Symposium

Financial markets increasingly react to social media discourse, yet investors lack tools to translate this unstructured commentary into measurable indicators. Platforms such as YouTube host extensive discussions about publicly traded equities, but extracting reliable sentiment trends from high-volume, noisy comment streams remains technically challenging. This project develops a stock sentiment and market intelligence platform that transforms YouTube comment data into aggregated sentiment indicators aligned to specific equities. Comments are mapped to equities using ticker specific keyword identification combined with contextual filtering to reduce false associations from ambiguous or off-topic mentions. The system assigns numerical sentiment scores to individual comments and …

Department Portfolio Web App*, Phillip Suvacarov, Tommy Aitchison

Campus Research Month

Southern Adventist University’s School of Computing produces numerous course projects, capstones, and research papers each year, yet there is no centralized, public showcase for this work. Our system provides a structured submission workflow for current and former students, faculty approval to ensure academic quality, and moderated commenting and likes to encourage constructive engagement. We outline the content model, role-based access control, and review queue, and describe search, tagging, and media support (including PDFs, images, and code links). By making student work visible beyond the classroom, the portfolio supports recruitment, alumni relations, and employer outreach while strengthening the School’s scholarly community.

Sau Physical Activity Website (Paw)*, Lisbette Sanchez, Alberto Elizondo, Caleb Tenold, Evelyn Shtereva, Siegwart Mayr

Campus Research Month

Problem: Southern’s Physical Activity Website (PAW) used to track physical activity from students and faculty was no longer functional. Aside from unsupported API versions, there was also an issue with authorization and role assignments.

Solution: Southern’s Center for Innovation and Research in Computing (CIRC) adopted the assignment of restructuring a new web application to track physical activity. This project focuses on building a secure and scalable architecture that connects user devices, third-party fitness APIs, and a centralized database to support activity tracking, workout analysis, and fitness history. By combining modern web development practices with API integration and backend data processing, …

Towards Physics-Informed Neural Networks For Simulating Multiphase Geothermal Convection​*, Daniel C. Patton, Andrew Harrison Eno

Campus Research Month

Water and steam flow through porous rock, transferring heat via conduction and buoyancy-driven convection caused by density differences. Traditional numerical methods (finite-volume/finite-element) model this well but can become memory-intensive and unstable for long, high-detail simulations. This work demonstrates a Physics-Informed Neural Network (PINN) using a finite-difference approach within the NVIDIA PhysicsNeMo framework to simulate magma chambers in 2D. Tested on the Rio Pisco pluton in Peru, results are compared with the USGS HYDROTHERM model. PINNs learn from physical laws, offering accurate, flexible solutions with less data and development effort.

Chat Component For Php Web Apps*, Linton W. Feitosa, Caleb N. Hoffman

Campus Research Month

Chat rooms are a common feature in much of today's software. While many web applications could benefit from them, developing individual chat implementations can be repetitive and time consuming. Furthermore, publicly available and integrable chat components are difficult to find.

We created a general-use chat component for PHP web applications using the Yii2 framework. Our component features chat rooms, asynchronous messaging, and contact management. It is widely applicable, customizable, documented, and can be easily extended by future developers.

Code Visualizer: An Interactive Code Visualization Tool, Tadd Trumbull

Campus Research Month

Code Visualizer is a web-based, interactive algorithm visualization tool designed to help introductory computer science students develop a deeper understanding of array searching and sorting algorithms. Code Visualizer presents a step-by-step simulation environment built on a restricted Python subset, which allows students to observe array traversal, index manipulation, and algorithmic operations in real time. The tool features two learning modes: View Mode and Predict Mode. The underlying architecture utilizes a behavioral software design pattern called command pattern.

Autologger: A Multi-Agent Framework For The End-To-End Automated Logging, Renyi Zhong, Yintong Huo, Wenwei Gu, Yichen Li, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Software logging is critical for system observability, yet developers face a dual crisis of costly overlogging and risky underlogging. Existing automated logging tools often overlook the fundamental whether-to-log decision and struggle with the composite nature of logging. In this paper, we propose AutoLogger, a novel hybrid framework that addresses the complete the end-to-end logging pipeline. AutoLogger first employs a fine-tuned classifier, the Judger, to accurately determine if a method requires new logging statements. If logging is needed, a multi-agent system is activated. The system includes specialized agents: a Locator dedicated to determining where to log, and a Generator focused on …

Chopchop: The Digital Cookbook, Dominc Mcdevitt, Shane Misley, Katie Cerda, Kobie Henson, Adolfo Duran

Presentations - 2026

Problem With traditional recipe organization methods,

● Recipes are scattered across paper, PDFs, Word docs, and notes

● Paper recipes can be lost, damaged, or left at home

● Digital recipes are difficult to edit, store, and organize

● Manually typing or updating recipes is time-consuming

● Sharing recipes is inconvenient and often confusing

● Limited or inconsistent cloud access reduces accessibility

● Formatting is messy and inconsistent across platforms

● No simple, centralized system for managing recipes

Budgeting Apps, Financial Literacy, And Financial Control, Max Masabo, Abdullah Mohammad Mahi

Presentations - 2026

Our paper shows the real hidden connections between budgeting app usage and financial wellbeing of U.S Households

Match-A-Fit, Adan Diaz De Leon, Juan Marco Saca Dada, Brianna Mendoza, Arsalan Kataneh, Theophile Nsabimana, Pedro Jacobo

Presentations - 2026

Welcome to Match-a-Fit! Match-a-Fit is an iOS application that allows the user to create a digital closet by uploading images of their clothing items. With AI, the program can generate outfits based on the digital closet, the time, and the occasion. Match-a-Fit’s purpose is designed to help users who struggle to get ready, run out of time, or can’t decide on an outfit, by easily generating outfit options based on the occasion.

Match-A-Fit, Brianna Mendoza, Adan Diaz De Leon, Pedro Jacobo, Juan Marco Saca Dada

Posters - 2026

Welcome to Match-a-Fit! Match-a-Fit is an iOS application that allows the user to create a digital closet by uploading images of their clothing items. With AI, the program can generate outfits based on the digital closet, the time, and the occasion. Match-a-Fit’s purpose is designed to help users who struggle to get ready, run out of time, or can’t decide on an outfit, by easily generating outfit options based on the occasion.

Maddenlite, Sergio Pena

Presentations - 2026

Problem •“What If” scenarios impossible to test accurately •Commercial games rely on arcade physics •Spreadsheets lack visual engagement

Motivation •Passion for football analytics •Desire to simulate cross-era matchups •Apply math models to real-world sports data

Solution •Python based simulation engine using historical play-by-play data •Simulates outcomes based on probability

A.I.R.E., Laurene Robinson

Presentations - 2026

•Cybersecurity analysts rely on reverse engineering to understand suspicious software. •Ghidra can surface decompiled code, but it does not fully explain function purpose, behavioral meaning, or analyst priority. •When symbols are stripped and context is weak, analysts must still reconstruct intent manually from low-level output. •That process is Time-consuming , complex and , operationally costly

Harvest Scanner, Alexander Murphy

Posters - 2026

In current times, people can find themselves at the whims of markets and may be spending more than they realize or want to on regular, everyday goods. New tools can help users keep track of the goods they are paying for. Harvest Scanner was developed to scan and track local grocery prices from stores using their publicly available website information. It was developed in Python using PyQt5 for GUI. The database is stored as an SQL file with Python using SQLite engine. Users will be able to view local grocery prices in a database interface (GUI). There are many features …

A.I.R.E. - Ai-Assisted Reverse Engineering, Laurene Robinson

Posters - 2026

Reverse engineering plays a vital role in cybersecurity by helping analysts examine unknown binaries, investigate malware, identify vulnerabilities, and better protect sensitive systems. However, once a program is compiled and stripped, the meaningful names that describe its behavior are lost, leaving behind generic function labels like FUN_00401a30. Analysts must then manually interpret decompiled code, trace call chains, and infer program behavior function by function, which is slow and mentally demanding on large binaries. To address this challenge, this project introduces A.I.R.E., a local Ghidra extension that extracts contextual evidence from stripped functions and uses a locally hosted language model to …

Topshelf, Ayden Jay Soliz

Posters - 2026

With so many great video games releasing each year, it becomes challenging to keep up with the latest. Players find it difficult to maintain an updated list of future games to play, and many existing online trackers have become too complicated to use. TopShelf is designed to be a simple video game backlogging website that will track games for the player. By connecting to an online video game database API, users can add/drop games from their personal list and enable tracking and receive emails for platform releasing. Gamers can leave all the tracking and updates responsibilities to TopShelf