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Articles 181 - 210 of 1844
Full-Text Articles in Computer Sciences
Exploring Neural Networks For Developing A Chess Learning Platform With Integrated Ai Agent, Lauren Escobedo
Exploring Neural Networks For Developing A Chess Learning Platform With Integrated Ai Agent, Lauren Escobedo
Posters - 2024
Chess is a highly strategic, complex, and long-form game that has been popular for many centuries. Due to the aforementioned complexities of this game, new players often have a hard time learning how to effectively and successfully play. With the recent developments in machine learning algorithms, new opportunities arise to create artificially intelligent tutors - not only for chess, but for all subjects. This project aims to develop a product which investigates the integration of an artificially intelligent “coach”, named Chesster, to train the player, which is trained on a neural network machine learning algorithm.
Gradual Memory Safety, Jack Phillips
Gradual Memory Safety, Jack Phillips
All NMU Master's Theses
This paper extends the theory of Gradual Types to include memory safe Region-Types and Region-Based Memory Management. It also makes advancements in the capabilities of Region-Based systems. Lastly, it presents the Svejk language and Hasek Type System.
Code Search Is All You Need? Improving Code Suggestions With Code Search, Junkai Chen, Xing Hu, Zhenhao Li, Cuiyun Gao, Xin Xia, David Lo
Code Search Is All You Need? Improving Code Suggestions With Code Search, Junkai Chen, Xing Hu, Zhenhao Li, Cuiyun Gao, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
Modern integrated development environments (IDEs) provide various automated code suggestion techniques (e.g., code completion and code generation) to help developers improve their efficiency. Such techniques may retrieve similar code snippets from the code base or leverage deep learning models to provide code suggestions. However, how to effectively enhance the code suggestions using code retrieval has not been systematically investigated. In this paper, we study and explore a retrieval-augmented framework for code suggestions. Specifically, our framework leverages different retrieval approaches and search strategies to search similar code snippets. Then the retrieved code is used to further enhance the performance of language …
Encoding Version History Context For Better Code Representation, Huy Nguyen, Christoph Treude, Patanamon Thongtanunam
Encoding Version History Context For Better Code Representation, Huy Nguyen, Christoph Treude, Patanamon Thongtanunam
Research Collection School Of Computing and Information Systems
With the exponential growth of AI tools that generate source code, understanding software has become crucial. When developers comprehend a program, they may refer to additional contexts to look for information, e.g. program documentation or historical code versions. Therefore, we argue that encoding this additional contextual information could also benefit code representation for deep learning. Recent papers incorporate contextual data (e.g. call hierarchy) into vector representation to address program comprehension problems. This motivates further studies to explore additional contexts, such as version history, to enhance models' understanding of programs. That is, insights from version history enable recognition of patterns in …
Large Language Model For Vulnerability Detection: Emerging Results And Future Directions, Xin Zhou, Ting Zhang, David Lo
Large Language Model For Vulnerability Detection: Emerging Results And Future Directions, Xin Zhou, Ting Zhang, David Lo
Research Collection School Of Computing and Information Systems
Previous learning-based vulnerability detection methods relied on either medium-sized pre-trained models or smaller neural networks from scratch. Recent advancements in Large Pre-Trained Language Models (LLMs) have showcased remarkable few-shot learning capabilities in various tasks. However, the effectiveness of LLMs in detecting software vulnerabilities is largely unexplored. This paper aims to bridge this gap by exploring how LLMs perform with various prompts, particularly focusing on two state-of-the-art LLMs: GPT-3.5 and GPT-4. Our experimental results showed that GPT-3.5 achieves competitive performance with the prior state-of-the-art vulnerability detection approach and GPT-4 consistently outperformed the state-of-the-art.
Unveiling Memorization In Code Models, Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, Donggyun Han, David Lo
Unveiling Memorization In Code Models, Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, Donggyun Han, David Lo
Research Collection School Of Computing and Information Systems
The availability of large-scale datasets, advanced architectures, and powerful computational resources have led to effective code models that automate diverse software engineering activities. The datasets usually consist of billions of lines of code from both open-source and private repositories. A code model memorizes and produces source code verbatim, which potentially contains vulnerabilities, sensitive information, or code with strict licenses, leading to potential security and privacy issues.This paper investigates an important problem: to what extent do code models memorize their training data? We conduct an empirical study to explore memorization in large pre-trained code models. Our study highlights that simply extracting …
Greening Large Language Models Of Code, Jieke Shi, Zhou Yang, Hong Jin Kang, Bowen Xu, Junda He, David Lo
Greening Large Language Models Of Code, Jieke Shi, Zhou Yang, Hong Jin Kang, Bowen Xu, Junda He, David Lo
Research Collection School Of Computing and Information Systems
Large language models of code have shown remarkable effectiveness across various software engineering tasks. Despite the availability of many cloud services built upon these powerful models, there remain several scenarios where developers cannot take full advantage of them, stemming from factors such as restricted or unreliable internet access, institutional privacy policies that prohibit external transmission of code to third-party vendors, and more. Therefore, developing a compact, efficient, and yet energy-saving model for deployment on developers' devices becomes essential.To this aim, we propose Avatar, a novel approach that crafts a deployable model from a large language model of code by optimizing …
Streamlining Java Programming: Uncovering Well-Formed Idioms With Idiomine, Yanming Yang, Xing Hu, Xin Xia, David Lo, Xiaohu Yang
Streamlining Java Programming: Uncovering Well-Formed Idioms With Idiomine, Yanming Yang, Xing Hu, Xin Xia, David Lo, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Code idioms are commonly used patterns, techniques, or practices that aid in solving particular problems or specific tasks across multiple software projects. They can improve code quality, performance, and maintainability, and also promote program standardization and reuse across projects. However, identifying code idioms is significantly challenging, as existing studies have still suffered from three main limitations. First, it is difficult to recognize idioms that span non-contiguous code lines. Second, identifying idioms with intricate data flow and code structures can be challenging. Moreover, they only extract dataset-specific idioms, so common idioms or well-established code/design patterns that are rarely found in datasets …
Improving Educational Delivery And Content In Juvenile Detention Centers, Yomna Elmousalami
Improving Educational Delivery And Content In Juvenile Detention Centers, Yomna Elmousalami
Undergraduate Research Symposium
Students in juvenile detention centers have the greatest need to receive improvements in educational delivery and content; however, they are one of the “truly disadvantaged” populations in terms of receiving those improvements. This work presents a qualitative data analysis based on a focus group meeting with stakeholders at a local Juvenile Detention Center. The current educational system in juvenile detention centers is based on paper worksheets, single-room style teaching methods, outdated technology, and a shortage of textbooks and teachers. In addition, detained students typically have behavioral challenges that are deemed "undesired" in society. As a result, many students miss classes …
Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin
Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin
Research Symposium
Carbon–carbon (C–C) bond activation has gained increased attention as a direct method for the synthesis of pharmaceuticals. Due to the thermodynamic stability and kinetic inaccessibility of the C–C bonds, however, activation of C–C bonds by homogeneous transition-metal catalysts under mild homogeneous conditions is still a challenge. Most of the systems in which the activation occurs either have aromatization or relief of ring strain as the primary driving force. The activation of unstrained C–C bonds of phosphaalkynes does not have this advantage. This study employs Density Functional Theory (DFT) calculations to elucidate Pt(0)-mediated C–CP bond activation mechanisms in phosphaalkynes. Investigating the …
Design Considerations For The Use Of The Julia Programming Language In Future Quantum Networking Simulation Software, Takashi Joubert
Design Considerations For The Use Of The Julia Programming Language In Future Quantum Networking Simulation Software, Takashi Joubert
Theses and Dissertations
Given the prevalence of Python-based packages in the existing quantum network simulation ecosystem, we attempt to assess what might be realistically gained by switching to Julia. We focus our experimental activities on three areas: 1) surveying the characteristics of Julia as they tie into robust framework development, 2) presenting benchmarks that compare Julia and Python with respect to elements of possible simulation workloads, and 3) producing a tangible lightweight Julia architecture for modeling components in a manner similar to SeQUeNCe. Our analysis suggests that while Julia does o.er performance advantages over Python over certain workloads, knowing the reasons for why …
Fixing Your Own Smells: Adding A Mistake-Based Familiarization Step When Teaching Code Refactoring, Ivan Wei Han Tan, Christopher M. Poskitt
Fixing Your Own Smells: Adding A Mistake-Based Familiarization Step When Teaching Code Refactoring, Ivan Wei Han Tan, Christopher M. Poskitt
Research Collection School Of Computing and Information Systems
Programming problems can be solved in a multitude of functionally correct ways, but the quality of these solutions (e.g. readability, maintainability) can vary immensely. When code quality is poor, symptoms emerge in the form of 'code smells', which are specific negative characteristics (e.g. duplicate code) that can be resolved by applying refactoring patterns. Many undergraduate computing curricula train students on this software engineering practice, often doing so via exercises on unfamiliar instructor-provided code. Our observation, however, is that this makes it harder for novices to internalise refactoring as part of their own development practices. In this paper, we propose a …
Broadening Participation Of Teachers In Computing: Examining Postsecondary Educational Experiences And Prospective Educators’ Cs Teaching Interests, Robert Schwarzhaupt, Alexsandra Galanis, Joanna Goode, Kate Blanchard, Jill Bowdon, Joseph P. Wilson
Broadening Participation Of Teachers In Computing: Examining Postsecondary Educational Experiences And Prospective Educators’ Cs Teaching Interests, Robert Schwarzhaupt, Alexsandra Galanis, Joanna Goode, Kate Blanchard, Jill Bowdon, Joseph P. Wilson
Journal of Computer Science Integration
Teacher shortages in K–12 computer science (CS) education negatively impact students’ access to CS courses, exposure to CS concepts, and interest in CS-related careers. To address CS teacher shortages, this study seeks to understand factors related to expressing a preference to teach CS among prospective teachers. The study team analyzed data from 27,700 prospective teacher applications accepted into the 2016–2020 Teach For America (TFA) corps (cohorts). The TFA corps is an alternative teacher development program that recruits and prepares participants to obtain their teaching certification while they work for at least two years in underserved communities on a temporary teaching …
What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman
What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman
Dissertations, Theses, and Capstone Projects
The word “billion” is a mathematical abstraction related to “big,” but it is difficult to understand the vast difference in value between one million and one billion; even harder to understand the vast difference in purchasing power between one billion dollars, and the average U.S. yearly income. Perhaps most difficult to conceive of is what that purchasing power and huge mass of capital translates to in terms of power. This project blends design, text, facts, and figures into an interactive narrative website that helps the user better understand their position in relation to extreme wealth: https://whatdoesonebilliondollarslooklike.website/
The site incorporates …
Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala
Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala
2024 REYES Proceedings
With advancements in AI-driven natural language generation, distinguishing between AI-generated and human-written text has become imperative for ensuring content authenticity across industries. This study explores the effectiveness of Bidirectional Encoder Representations from Transformers (BERT) in addressing this classification challenge. Utilizing a diverse dataset and robust preprocessing techniques, BERT achieved a peak F1-score of 0.94364, outperforming traditional models such as Logistic Regression and Support Vector Machines. The results underscore the potential of transformer-based models in addressing real-world con- tent verification problems. Future enhancements include fine-tuning and expanding datasets for greater generalizability.
The Computational Search For Unidentified Central Configurations Of The Newtonian N-Body Problem, Hannah G. Havel
The Computational Search For Unidentified Central Configurations Of The Newtonian N-Body Problem, Hannah G. Havel
CURE Proceedings
The N-body problem is a field of study in mathematics and physics that involves predicting the motion of particles moving under their mutual gravitational attraction. It is vital in celestial mechanics, such as planning collision-free satellite orbit trajectories. When beginning to understand the N-body problem, we can start by looking at equal masses of these particles or celestial bodies. As particles move, their position and velocity change, both energy and angular momentum are conserved. Sets of constant energy and angular momentum, known as integral manifolds, are higher-dimensional figures that represent constraints of movement to a system. Integral manifolds are described …
Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers
Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers
All Master's Theses
The development of electric vehicles is currently considered one of the most innovative areas in manufacturing. Largely driven by the desire to reduce greenhouse emissions, electric vehicles are seen as a viable alternative to internal combustion engine cars. Starting from consumer cars, a dedicated effort is being made to translate this into commercial vehicles for freight and delivery. This research introduces a novel adaptive Nawaz, Enscore, Ham (NEH) algorithm with constrained nearest neighbor subtour (NEH-NN). This algorithm is tested on the standard benchmark problems in literature and used as a seed solution for the Genetic Algorithm (GA). The performance and …
Ung: A Diagnostic Standard C Library, Jakob Knute Kaivo
Ung: A Diagnostic Standard C Library, Jakob Knute Kaivo
Graduate Theses, Dissertations, and Problem Reports (ETD)
Undefined behavior in C programs is a major source of unreliable software. Many of the most common exploitable software vulnerabilities can be traced directly to undefined behavior. In the increasingly connected world, a successful attack can cost the victim millions of dollars to recover from. While static program analysis aids in identifying undefined behavior, testing indicates that even the best static analysis tools correctly identifies about 35% of these defects. This dissertation introduces UNG’s Not GNU (UNG), a standard C library designed to mitigate undefined behavior. Where others have seen opportunities for optimization, UNG makes every effort to identify undefined …
The Amethyst Compiler, David Britton
The Amethyst Compiler, David Britton
Williams Honors College, Honors Research Projects
Amethyst is a custom programming language, whose compiler translates Amethyst source code into textual LLVM IR, which can, in turn, be compiled by LLVM back-ends to produce executable binaries. This paper explores compiler concepts and implementation details for the Amethyst compiler, describes the LLVM architecture, and provides an overview of some Amethyst language features.
Statically Controlled Synchronized Lane Architectures, Scott K. Pomerville
Statically Controlled Synchronized Lane Architectures, Scott K. Pomerville
Dissertations, Master's Theses and Master's Reports
Modern superscalar processors dominate the field of computing. While dynamic execution allows for versatility in code, these processors are complex. Statically scheduled code has historically enabled simpler processor designs, but static scheduling cannot account for variables that are unknown at compile time. Furthermore, static scheduling has many inefficiencies, such as the need to insert a large number of nops for code in traditional Very Long Instruction Word (VLIW) processors. In this dissertation, we explore a novel architectural approach for statically scheduled code by breaking the code into several synchronous instruction streams. By representing code in a fundamentally new way, we …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
College of Graduate Studies: Theses & Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
A Critical Computing Curriculum Design Case: Exploring Tribal Sovereignty For Middle School Students, Kristin A. Searle, Aubrey Rogowski, Colby Tofel-Grehl, Mengying Jiang
A Critical Computing Curriculum Design Case: Exploring Tribal Sovereignty For Middle School Students, Kristin A. Searle, Aubrey Rogowski, Colby Tofel-Grehl, Mengying Jiang
Journal of Computer Science Integration
We report on our efforts to design an integrated computing curriculum for middle school students in Montana that is in line with the Kapor Center’s focus on culturally sustaining-revitalizing pedagogies. Montana provides a unique context for doing this work because a state constitutional mandate requires all K-12 students to learn about tribal histories and cultures through Indian Education For All (IEFA). IEFA centers around seven essential understandings about Indigenous peoples in Montana that are integrated across content areas. In addition, implementation of Montana’s CS standards began in the 2021–2022 school year. In the curricular design, we sought to bring together …
Employing An Abolitionist, Critical Race Pedagogy In Cs: Centering The Voices, Experiences And Technological Innovations Of Black Youth, Tiera Tanksley
Employing An Abolitionist, Critical Race Pedagogy In Cs: Centering The Voices, Experiences And Technological Innovations Of Black Youth, Tiera Tanksley
Journal of Computer Science Integration
This paper proposes a pedagogical extension of culturally responsive praxis called abolitionist, critical race pedagogy in CS. To showcase the power and potentiality of this pedagogy, this paper examines the experiences of 2 cohorts of Black high school students (n = 30) who participated in a critical race technology course that was taught during the dual pandemic of COVID-19 and anti-Black racism. The goal of this summer course was to employ an abolitionist, critical race pedagogy in CS to foster Black students’ ability to critically examine the ubiquity of anti-Black racism within the socio-technical architectures (e.g. code, data, algorithms and …
Culturally Responsive-Sustaining Computational Thinking: Enactment In Elementary Classrooms, Victoria Macann, Aman Yadav
Culturally Responsive-Sustaining Computational Thinking: Enactment In Elementary Classrooms, Victoria Macann, Aman Yadav
Journal of Computer Science Integration
Technology has increasingly permeated many aspects of everyday life and this evolution raises the need for individuals to understand how the digital world works and what opportunities and risks it brings (Nouri, Zhang, Mannila & Norén, 2019). For this to be an experience for everyone, we need to rethink how we integrate computational thinking (CT) and provide teachers with tools to center their students’ identities, experiences, and cultures in the classroom. In this paper, we present two case studies of primary (elementary) teachers from a full primary (student ages 5–13) semi-rural school in the North Island of New Zealand that …
Choosing A Sophisticated, Robust, And Secure Programming Language, J. Simon Richard
Choosing A Sophisticated, Robust, And Secure Programming Language, J. Simon Richard
The Downtown Review: An Interdisciplinary Journal Written and Peer-Reviewed by Mandel Honors College Students at Cleveland State University
This paper explores which programming languages maximize the quality and efficiency of software development projects requiring high levels of sophistication, security, and stability. Of the four languages discussed in this paper—C, C++, Java, and Rust—we conclude that Rust is the best for this application.
Μakka: Mutation Testing For Actor Concurrency In Akka Using Real-World Bugs, Mohsen Moradi Moghadam, Mehdi Bagherzadeh, Raffi Khatchadourian, Hamid Bagheri
Μakka: Mutation Testing For Actor Concurrency In Akka Using Real-World Bugs, Mohsen Moradi Moghadam, Mehdi Bagherzadeh, Raffi Khatchadourian, Hamid Bagheri
Publications and Research
Actor concurrency is becoming increasingly important in the real-world and mission-critical software. This requires these applications to be free from actor bugs, that occur in the real world, and have tests that are effective in finding these bugs. Mutation testing is a well-established technique that transforms an application to induce its likely bugs and evaluate the effectiveness of its tests in finding these bugs. Mutation testing is available for a broad spectrum of applications and their bugs, ranging from web to mobile to machine learning, and is used at scale in companies like Google and Facebook. However, there still is …
Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum
Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum
Honors Theses
Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …
A Comprehensive Evaluation Of Large Language Models On Legal Judgment Prediction, Ruihao Shui, Yixin Cao, Xiang Wang, Tat-Seng Chua
A Comprehensive Evaluation Of Large Language Models On Legal Judgment Prediction, Ruihao Shui, Yixin Cao, Xiang Wang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4’s law evaluation raise questions concerning their performance in real-world legal tasks. To systematically investigate their competency in the law, we design practical baseline solutions based on LLMs and test on the task of legal judgment prediction. In our solutions, LLMs can work alone to answer open questions or coordinate with an information retrieval (IR) system to learn from similar cases or solve simplified multi-choice questions. We show that similar cases and multi-choice options, namely label candidates, included in prompts …
Wsdms: Debunk Fake News Via Weakly Supervised Detection Of Misinforming Sentences With Contextualized Social Wisdom, Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Zhiwei Yang
Wsdms: Debunk Fake News Via Weakly Supervised Detection Of Misinforming Sentences With Contextualized Social Wisdom, Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Zhiwei Yang
Research Collection School Of Computing and Information Systems
In recent years, we witness the explosion of false and unconfirmed information (i.e., rumors) that went viral on social media and shocked the public. Rumors can trigger versatile, mostly controversial stance expressions among social media users. Rumor verification and stance detection are different yet relevant tasks. Fake news debunking primarily focuses on determining the truthfulness of news articles, which oversimplifies the issue as fake news often combines elements of both truth and falsehood. Thus, it becomes crucial to identify specific instances of misinformation within the articles. In this research, we investigate a novel task in the field of fake news …
Supporting Software Engineers With Large Language Model-Based Automation, Ting Zhang
Supporting Software Engineers With Large Language Model-Based Automation, Ting Zhang
Dissertations and Theses Collection (Open Access)
In recent years, software engineering (SE) has witnessed significant growth, leading to the creation and sharing of an abundance of software artifacts such as source code, bug reports, and pull requests. Analyzing these artifacts is crucial for comprehending the sentiments of software developers and automating various SE tasks, ultimately leading to more human-centered automated SE and enhancing software development efficiency. However, the diverse and unstructured nature of software text poses a significant challenge to this analysis. In response, researchers have investigated a variety of approaches, including the utilization of natural language processing techniques. The advent of large language models (LLMs), …