Software Engineering Commons^™

Synthergy: Social Deduction And Deception In Llm-Powered Agents, Lauren Campbell, Andrew Forney

Honors Thesis

Synthergy is an online social deduction game designed to enable comparative analysis of how large language model-powered agents engage in social deduction and deception under conditions of asymmetric information. Inspired by social deduction games such as Town of Salem, Throne of Lies, and Mafia, the game consists of two factions, Harmony and Discord, to which agents are secretly assigned. Agents must infer others’ affiliations through dialogue, in-game abilities, and voting behavior. To evaluate agent behavior, we conducted 100 simulated games across six agent types: a random baseline agent (RandomSynth), an LLM-based agent (Synth), a chain-of-thought agent (CoT Synth), a Bayesian …

Development And Launch Of Abn: An Adventist Freelance Web Application, Abishur Moses-Pakkianathan

MS in Computer Science Project Reports

The Seventh-day Adventist community often relies on personal networks and word-of-mouth for Adventist business services. Many of these businesses meet and provide services to their clients primarily through church connections and community recommendations. As the community and businesses grow, traditional networking methods become increasingly difficult to maintain. General marketplaces lack the trust framework shared by Adventists, and faith-based directories are often static or outdated without booking capabilities. Our solution provides a reliable and modern platform for Adventists to create service listings, receive and manage bookings, and connect with faith-aligned clients.

Nutrilog: Design And Development Of A Full-Stack Web Application For Holistic Health Tracking, Jaromir J. Saloni

Honors Theses

NutriLog is a web-based fitness and nutrition tracking application designed to help users record, organize, and interpret personal health data in one centralized platform. Many existing applications focus primarily on either nutrition tracking or exercise performance, which can make it difficult for users to understand how food intake and physical activity interact. NutriLog addresses this gap by combining food logging, exercise logging, calorie adjustment, nutrition summaries, and historical tracking into a single dashboard-based interface.

The application was developed using React and TypeScript for the frontend and Supabase for authentication, database storage, and user-specific data management. Nutrition data is supported through …

Developing Narrative-Based Stem Learning Tool For K-6 Visually Impaired Students, Daniel Tsivkovski, Dylan Ravel, Jeffrey Kraskouskas, Brandon Foley, Maryam Etezad, Franceli Cibrian, Rajeev Joshi, Ariel Han

Student Scholar Symposium Abstracts and Posters

This research develops a free, accessible web application that enables K-6 students who are blind or visually impaired (BVI) to learn STEM concepts using refreshable braille displays. Currently, most online learning tools are not designed for BVI students, creating a significant educational barrier.

The application interfaces with commercial braille displays and uses narrative-based learning to make STEM content approachable and engaging. By presenting material as personalized interactive stories generated with the help of Artificial Intellligence (AI), students can connect with concepts while developing braille reading skills. The curriculum design prioritizes accessibility through the Accessible Rich Internet Applications (ARIA) standards and …

Online Legislation: Developments And Trends In Data Privacy And Software Development, Garrett J. Splinter

Honors Program: Senior Projects (Public)

The increasingly relevant interaction between the law and data privacy, as well as compliance requirements enforced by the United States, is currently in a state of transition. Various states, such as California, Colorado, Connecticut, Nebraska, and many others, all have passed legislation with varied requirements and definitions that make for a challenging framework in which software developers operate, as the universal nature of the internet renders their compliance with current legislation a challenge. Enforcement also tends to be relatively relaxed in most modern examples, though it has escalated after 2020, and this trend may continue in the future, lending credence …

Selective Concolic Testing, Guofeng Zhang, Zhenbang Chen, Ziqi Shuai, Jun Sun, Weijiang Hong, Yufeng Zhang, Ji Wang, Yang Liu

Research Collection School Of Computing and Information Systems

The principled combination of symbolic execution and random testing lacks a formal foundation, especially in deciding which inputs to symbolize. We propose selective concolic testing, a cost-aware framework that formulates this choice as an optimized policy problem of a MDP (Markov Decision Process). We model program exploration over a finite control-flow graph, where MDP states represent covered statements, actions partition path constraints into symbolic and random fragments, rewards reflect coverage gain, and costs account for SMT solving effort and sampling inefficiency. Our framework yields the first formal characterization of selective symbolization as policy synthesis in a probabilistic system. We prove …

Gencode: A Generic Data Augmentation Framework For Boosting Deep Learning-Based Code Understanding, Zeming Dong, Qiang Hu, Xiaofei Xie, Maxime Cordy, Mike Papadakis, Yves Le Traon, Jianjun Zhao

Research Collection School Of Computing and Information Systems

Pre-trained code models lead the era of code intelligence, with multiple models designed with impressive performance. However, one important problem, data augmentation for code data that automatically helps developers prepare training data lacks study in this field. In this paper, we introduce a generic data augmentation framework, GenCode, to enhance the training of code understanding models. Simply speaking, GenCode follows a generation-and-selection paradigm to prepare useful training code data. Specifically, it employs code augmentation techniques to generate new code candidates first and then identifies important ones as the training data by influence scores. To evaluate the effectiveness of GenCode, we …

Pyspqr: A Python Package For Density Estimation Using Deep Learning, Cameron Eddy, Reetam Majumder

Electrical Engineering and Computer Science Undergraduate Honors Theses

Splines are used for representing complex functions. In statistics, splines can be used for distributional shapes that are difficult to model by traditional parametric approaches. Ramsay (1) uses M-Spline bases to estimate continuous distributions. Semi-Parametric Quantile Regression (SPQR), developed by Xu and Reich (2), models conditional distributions where a neural network is used to estimate the basis function weights that depend on covariates. (3) implements a package for SPQR in R. We build on this by implementing a version of SPQR in Python with PyTorch. By using PyTorch, we can use more sophisticated deep learning architectures than those available in …

Software Integration In Personal Healthcare Devices And The Patient User Experience, Yassine Chahid, Patrick Slattery

Publications and Research

This study examines the current landscape and future direction of medical device hardware and software integration, focusing on how each contributes to patient care. It begins by analyzing hardware focused medical devices, such as implantable tools patients may rely on to assist with their condition, alongside diagnostic and monitoring equipment used to treat conditions in a variety of medical areas (e.g. cardiovascular conditions). It then evaluates how software is currently integrated through embedded systems, data processing, and user interfaces that support real time monitoring and clinical decision making, and how this impacts quality of care for the patient whilst minimizing …

Weavecc: Symbolically-Guided Joint Exploration Of Inputs And Schedules For Concurrency Bug Detection, William Philip Dinauer

Dartmouth College Master’s Theses

Concurrent programs introduce a class of bugs that depend jointly on both program inputs and thread schedules. Exposing these bugs requires simultaneously reasoning about which code paths are reachable and which thread interleavings are possible. At the same time, many existing tools handle the problem insufficiently. Race detectors observe only the interleavings that the OS happens to produce. Fuzzers explore inputs without controlling schedules. Tools that address both dimensions together exist, but are built on interpretation-based symbolic executors that incur considerable overhead.

We present WeaveCC, a practical concurrency testing tool for C/C++ programs that jointly explores inputs and thread schedules. …

Func: Reducing The Impact Of Android Framework Evolution On Malware Detection, Hailong Yu, Tiantian Wang, Lwin Khin Shar, Hanmeng Li, David Lo

Research Collection School Of Computing and Information Systems

Android malware detection approaches commonly use APIs and permissions as features for classifying malware. However, since the release of the first Android operating system in 2008, the Android framework has undergone numerous version updates. The evolution of the Android framework over time has led to changes in APIs and permissions, including deprecations and replacements. These changes can result in inaccurate characterization of Android malware, thereby affecting performance of malware detectors. There is a lack of methods to mitigate the impact of Android framework evolution on malware detection. To fill this gap, we conduct a systematic study of the impact of …

Autonomous Deficiency Detection And Vision-Language Summarization For Underground Infrastructure On Embedded Edge Systems, Johny Lopez

LSU New Orleans Theses and Dissertations

Aging underground infrastructure poses significant risks to public health and environmental safety, yet structural condition assessment remains bottlenecked by labor-intensive manual CCTV inspections. This thesis proposes a comprehensive algorithmic framework enabling fully autonomous, real-time deficiency detection, geometric assessment, and natural language reporting on resource- constrained edge computing platforms. Three core components address this challenge. First, RAPID-SCAN, a novel semantic segmentation architecture utilizing a Dynamic Feature Pyramid Network and Channel-Spatial Attention, achieves real-time, pixel-precise defect localization with dramatically reduced parameters. Second, an Edge-Optimized Vision-Language Model pipeline employing LoRA and 4-bit QLoRA quantization compresses Phi-3.5 for local deployment, en- abling autonomous technical …

Post-Quantum Cryptography Encryption Implementation For Messaging App, Callum S. Ward

Theses/Capstones/Creative Projects

This paper and complementary capstone project aim to explore the state of post-quantum cryptography today by defining the algorithms with which quantum computers can decipher modern asymmetric cryptographic algorithms in exponentially accelerated time, exploring national standards body NIST’s recommendations to circumvent these weaknesses with post-quantum solutions, and implementing recommended algorithms in my group’s project for the UNO Computer Science Capstone course, LockTalk. After having decided on ML-KEM for quantum-resistant asymmetric key transfer and AES-256 for symmetric message encryption and decryption, I was able to cryptographically encode messages to obscure their plaintext values from communication interceptions without any discernible increase in …

Know Thy Enemy: Building A Command-And-Control Solution For Adversarial Emulation, Caleb J. Chen

Senior Honors Theses

Command and Control (C2) is a critical part of any cyberattack. It serves many purposes, including Distributed Denial of Service (DDoS) attacks, data exfiltration, and malware deployment. Consequently, C2 frameworks play an important part in red team engagements and adversary emulation. However, many adversary emulation solutions focus on comprehensive testing through sequential technique execution instead of realistic chained and automated attacks. The proposed solution is Centurion, an open-source C2 framework that integrates MITRE's ATT&CK framework and several cybersecurity tools into modular playbooks for effective threat emulation. This paper provides background by defining key terms and concepts before delving into a …

Open Source Software Development Tool Installation: Challenges And Strategies For Novice Developers, Larissa Salerno, Christoph Treude, Patanamon Thongtanunam

Research Collection School Of Computing and Information Systems

As the world of technology advances, so do the tools that software developers use to create new programs. In recent years, software development tools have become more popular, allowing developers to work more efficiently and produce higher-quality software. Still, installing such tools can be challenging for novice developers at the early stage of their careers, as they may face issues such as compatibility problems (e.g., with operating systems) and unclear instructions. Therefore, this work aims to investigate the challenges novice developers face when installing software development tools and the strategies they employ to overcome them. To investigate these, we conducted …

Securing Cloud-Native Systems: From Vulnerability Analysis To External And Insider Threat Detection, Jiongchi Yu

Dissertations and Theses Collection (Open Access)

Cloud-native systems have become the backbone of modern software infrastructure. However, their dynamic resource orchestration and complex configurability introduce a large attack surface and intricate security challenges. Adversaries can externally exploit vulnerabilities in cloud components or perform insider movement within cloud environments to launch attacks. As these systems increasingly support critical services, security breaches can lead to severe operational and economic consequences.

Despite extensive efforts in vulnerability detection and attack monitoring, existing approaches struggle to remain effective in cloud-native environments characterized by rapid evolution and inherent heterogeneity. In particular, they exhibit three fundamental limitations: (1) Insufficient understanding of defect patterns …

Post-Vote Tampering In Nigerian Elections And The Role Of Blockchain-Enabled Electoral Systems, Ransome Chukwubuikem Enechukwu

Electronic Theses and Dissertations

Post-vote tampering during the collation and transmission of election results remains a persistent challenge in Nigerian elections, enabling manipulation of already-cast votes and weakening public trust in electoral outcomes. Existing technological interventions, including biometric voter accreditation and digital result transmission systems, improve voter authentication but do not adequately secure the post-vote result collation process. This thesis proposes a blockchain-enabled framework designed to protect the integrity of election results during the collation and transmission stages. Using a Design Science Research methodology, the study develops a permissioned blockchain framework based on Hyperledger Fabric that records polling-unit results as immutable ledger entries and …

Sql Query Optimization - Human Vs. Chatgpt, Hailey Dennis

All Graduate Reports and Creative Projects, Fall 2023 to Present

Large Language Models (LLMs) such as ChatGPT have become ubiquitous tools for working professionals in the software industry. Many engineers are finding new ways to increase productivity by offloading tasks onto LLMs, while others are finding it difficult to trust code produced artificially, even after review. Taking a look at both perspectives, this study aims to compare a human’s ability to optimize SQL queries to that of an LLM and assess the experience using both methods.

Manual query optimization is a tedious task that relies heavily on statistics, heuristics, and good intuition. The SQL developer must search for the optimal …

The Quality Assurance Machine – A Software Quality Assurance Architecture For Ml-Enabled Systems, Shane E. Downing

All-Inclusive List of Electronic Theses and Dissertations

This dissertation evaluates whether a reusable assurance architecture, the Quality Assurance Machine (QAM), can provide effective product and process quality assurance for ML-enabled software platforms. The QAM is a system-level SQA architecture that turns plans and policies into versioned configurations, executes them in controlled environments, and produces preserved run evidence that supports traceability, auditability, and controlled change. The study follows Design Science Research and evaluates the instantiated artifact using eight assurance requirements (AR1–AR8) synthesized from standards-based guidance, including IEEE 730 and ISO/IEC/IEEE 15026. A four-year longitudinal evaluation combines two methods. First, operational evidence from routine regression and release-validation runs, defect …

Collaborative Practices And Tool Utilization In Software Development Projects: A Student Perspective, Yi Meng Lau, Muhammad Syahmi Bin Abbas, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Software development is a collaborative activity that depends on effective teamwork, shared understanding, and coordinated use of development practices and tools. While these aspects are well studied in professional environments, they are less frequently examined within software engineering education. This study investigates how students collaborate in group projects, focusing on collaborative practices, tool usage, and their perceptions of software quality. We conducted a quantitative post-project survey with 143 second-year undergraduate students enrolled in a software development course. The results show that students actively share information and often establish team norms to support coordination and collaboration. However, students face challenges in …