Open Access. Powered by Scholars. Published by Universities.®
Programming Languages and Compilers Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Systems Architecture (6)
- Other Computer Sciences (5)
- Software Engineering (4)
- Cybersecurity (3)
- Data Science (3)
-
- Education (3)
- Graphics and Human Computer Interfaces (3)
- Information Security (3)
- Art and Design (2)
- Artificial Intelligence and Robotics (2)
- Arts and Humanities (2)
- Higher Education (2)
- Instructional Media Design (2)
- OS and Networks (2)
- Theory and Algorithms (2)
- Business (1)
- Business Analytics (1)
- Computer Engineering (1)
- Computer and Systems Architecture (1)
- Curriculum and Instruction (1)
- Databases and Information Systems (1)
- Educational Technology (1)
- Engineering (1)
- Environmental Sciences (1)
- Graphic Design (1)
- Hardware Systems (1)
- Interdisciplinary Arts and Media (1)
- Institution
- Keyword
-
- Python (4)
- Computer science (3)
- Programming (3)
- Art and Art History (2)
- Programming languages (2)
-
- ALU and operations (1)
- ARMv7 (1)
- Active learning (1)
- Adversarial Examples (1)
- Adversarial Training (1)
- Analytics (1)
- Arkansas Tech University (1)
- Assembly language (1)
- Binge-watching; organized (1)
- C++ (1)
- CIFAR-10 (1)
- CPU (1)
- Chess; Game; Network Machine Learning Algorithm; Artificially Intelligent Tutors (1)
- Clojure (Computer program language); Computer programming; Error messages (Computer science) (1)
- Clojure (Computer program language); Error messages (Computer science) (1)
- Component nesting (1)
- Computer Science (1)
- Computer organization (1)
- Computer programming: C++ (Computer program language) (1)
- Course management system (1)
- Fantasy Football (1)
- Football analytics (1)
- Game engines (1)
- Game-based learning system (1)
- Incomplete designators (1)
- Publication
-
- Shelby Hall Graduate Research Forum Posters (5)
- Mathematics, Physics, and Computer Science Faculty Books and Book Chapters (3)
- Computer Science and Information Technology Grants Collections (2)
- Posters - 2025 (2)
- Posters - 2026 (2)
-
- ATU Faculty OER Books and Materials (1)
- All Assignment Prompts (1)
- All Open Educational Resources (1)
- Assignment Prompts (1)
- Cybersecurity: Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment (1)
- Mavs Open Press Open Educational Resources (1)
- Open Educational Resources (OER) (1)
- Poster Presentations (1)
- Posters - 2024 (1)
- Presentations - 2026 (1)
- Systems Manuals - 2026 (1)
- UROP Posters (1)
- Undergraduate Research Symposium 2024 (1)
- Undergraduate Research Symposium 2025 (1)
- File Type
Articles 1 - 28 of 28
Full-Text Articles in Programming Languages and Compilers
Computer Organization And Assembly Language Programming, Chenxi Wang Phd, Muhammad Rashed Phd
Computer Organization And Assembly Language Programming, Chenxi Wang Phd, Muhammad Rashed Phd
Mavs Open Press Open Educational Resources
Computer Organization and Assembly Language Programming is an open textbook written for CSE 2312 students at The University of Texas at Arlington and for anyone who wants to see clearly how high-level code becomes machine operations. The book takes the position that assembly is not a historical curiosity but a working tool: it is where system programming, embedded development, performance tuning, and real debugging skill begin.
Across sixteen chapters, this textbook builds from number systems and base conversion through ALU operations, status flags, and shift operations, then into ARMv7 assembly syntax, the load and store architecture, endianness, addressing modes, branch …
Maddenlite, Sergio Pena
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
Spinlock Game Engine, Shane Misley
Spinlock Game Engine, Shane Misley
Posters - 2026
Modern game engines prioritize developer convenience at the cost of performance and transparency. Large frameworks like Unity and Unreal Engine abstract away implementation details, which simplifies development but introduces computational overhead—often 40-50% of CPU and memory usage goes to engine infrastructure rather than the actual game. For developers targeting low-end hardware, older systems, or performance-critical applications, this overhead becomes prohibitive. The Spinlock Engine addresses this problem by adopting a "close-to-the-metal" philosophy, stripping away unnecessary abstraction layers to deliver raw speed and predictable behavior. Built in C++ with SDL3 and Raylib, Spinlock prioritizes memory efficiency, CPU optimization, and developer transparency—allowing you …
Maddenlite, Sergio Pena
Maddenlite, Sergio Pena
Posters - 2026
Sports simulations often rely on opaque, proprietary algorithms (like EA's Madden NFL). MaddenLite bridges the gap between sports analytics and interactive gaming by utilizing historical NFL Play-by-Play (PBP) data to drive a transparent, mathematically accurate simulation engine. The goal was to create a lightweight, UI-driven desktop application where users can simulate cross-era matchups (e.g., 2007 Patriots vs. 2025 Chiefs), manipulate rosters, and simulate entire seasons complete with official NFL tiebreaker protocols.
Stock Market Price Prediction Using Big Data Models Comparison Analysis, Vibhor Pal
Stock Market Price Prediction Using Big Data Models Comparison Analysis, Vibhor Pal
Shelby Hall Graduate Research Forum Posters
The stock market consists of complex financial datasets, and achieving stock price real time prediction needs an efficient big data framework for processing. This paper compares big data distributed data processing frameworks for forecasting stock prices using Graph Neural Networks (GNNs) - Apache Flink and Apache Spark. We analyze 70 publicly traded companies’ monthly data for the last 5 years from Yahoo Finance, ranked by Price-to-Earnings (P/E). In the companies’ datasets, there may be a connection or similarity between companies, and this can lead to similar stocks’ price behavior. These interfirm relationships are maintained by GNNs models, and their output …
Llm-Driven Weekly Newsletter To Assess Open Source Software Project Github Health, Christian Novalski, Christopher Chavez, Ghalian Fayyadh, Kostadin Damevski
Llm-Driven Weekly Newsletter To Assess Open Source Software Project Github Health, Christian Novalski, Christopher Chavez, Ghalian Fayyadh, Kostadin Damevski
UROP Posters
Open Source Software (OSS) projects increasingly depend on a diverse set of contributors, including episodic participants who contribute intermittently. Episodic contributors represent a large portion of OSS communities, yet projects often struggle to retain them, leading to decreased project health and continuity. While dashboards and real-time communication tools support continuously active contributors, they often fail to serve the unique needs of episodic participants, who may struggle to remain informed and re-engage with project activity after periods of absence. In this study, we examine the effect of a weekly, email-based newsletter intervention designed to improve awareness and engagement among episodic OSS …
Introduction To C++ (Volume I), Hussam Ghunaim Ph.D.
Introduction To C++ (Volume I), Hussam Ghunaim Ph.D.
All Open Educational Resources
This book is written as an Open Education Resource (OER) to replace expensive commercial materials currently used at the Department of Computer Science at Fort Hays State University. It has two volumes corresponding to the CSCI 121 and CSCI 221 courses. These courses are developed to introduce college freshmen students to Object-Oriented Programming utilizing C++. The author tried to bridge the gap in the current programming textbooks by avoiding lengthy and, on many occasions, unnecessary details. This book’s main feature is to present the discussed principles in the least wording possible while providing adequate examples and exercises to reinforce students’ …
Rattler Python, Samer Jabor
Rattler Python, Samer Jabor
Systems Manuals - 2026
The Rattler Python project is an interactive game-based learning system that intends to teach the basic concepts of Python programming through guided instruction, gameplay challenges, and review-based assessments. The document contains a proposal for this system consisting of problem definition, background research, existing solutions, and the proposed product, together with the system scope, assumptions, and the organization of the remainder of this document.
Breaking Down Terminology Of Clojure Error Messages For Beginner Programmers, John Walbran, Jaydon Stanislowski, Tristan Kalvoda
Breaking Down Terminology Of Clojure Error Messages For Beginner Programmers, John Walbran, Jaydon Stanislowski, Tristan Kalvoda
Undergraduate Research Symposium 2025
The Clojure programming language has educational potential for beginner programmers due to its clean, simple syntax and its strong focus on functional programming, an important aspect of CSci education. However, one weakness of Clojure lies in its error messages, which are messages that programmers receive when a program goes wrong. The terminology and shorthands used to convey necessary information for understanding the error are often confusing to novices. The issue is exacerbated by the fact that the error messages are phrased in terms of the underlying programming language – Java – which beginner programmers may typically be unfamiliar with. A …
Binge Buddies, Joshua Uribe
Binge Buddies, Joshua Uribe
Posters - 2025
Many people struggle to keep track of the shows and movies they’ve watched or plan to watch. Existing streaming platforms often provide limited or cluttered tracking features, making it challenging to stay organized. Binge Buddies addresses this issue by centralizing watchlists and viewing history in one streamlined location. The website is designed to simplify the binge-watching experience, helping users stay on top of their content and discover new shows/movies. Which makes the experience a smoother and more enjoyable experience.
Cyber Safe, Hiram Franco, Laurene Robinson, Joshua Do, Enrique Martinez, Han Vu
Cyber Safe, Hiram Franco, Laurene Robinson, Joshua Do, Enrique Martinez, Han Vu
Posters - 2025
With the rapid rise of cyber threats, understanding malware behavior is more crucial than ever. Millions of new malware variants emerge annually, compromising personal data, financial information, and entire networks. While no system is entirely immune, cybersecurity education can help mitigate risks. CYBERSAFE is a sandbox malware analyzer designed to enhance malware detection and analysis skills. By running malware samples in a controlled virtual environment, users can observe real-time file modifications, network activity, and system changes. The tool also includes interactive exercises and quizzes to reinforce learning. CYBERSAFE bridges the gap between theory and practice, providing hands-on experience to help …
Turbulence Prediction Using Non-Linear Phase Space Analysis, Jeremy Quijano
Turbulence Prediction Using Non-Linear Phase Space Analysis, Jeremy Quijano
Shelby Hall Graduate Research Forum Posters
Our research presents a novel approach for turbulence prediction in computational fluid dynamics (CFD) simulations using a non-linear phase space analysis (NLPSA) and threshold algorithm. NLPSA has been utilized in medical applications to predict seizures, as well as in cybersecurity to detect malicious control and utilization of computing systems. NLPSA uses time-series data to learn the normal operating state of the system, then sets a threshold to predict when the system becomes abnormal. Turbulence prediction is similar, such that a fluid system changes from normal to abnormal. Turbulence prediction methods currently utilize machine learning tools, such as convolutional neural networks …
Establishing A Framework For Evaluating Machine Learning Performance And Security Across Computational Ecosystems, Krista Stacey, Todd R. Andel
Establishing A Framework For Evaluating Machine Learning Performance And Security Across Computational Ecosystems, Krista Stacey, Todd R. Andel
Shelby Hall Graduate Research Forum Posters
The rapid evolution of computational ecosystems—ranging from embedded systems and cloud platforms to hybrid and quantum architectures—has introduced new challenges in deploying machine learning (ML) applications. While cloud computing offers scalability, it comes with increased latency and security risks, whereas edge computing, such as FPGA-based systems, provides real-time processing with constrained resources. Hybrid and quantum ecosystems further complicate decision-making, requiring careful trade-offs between performance and security. This research seeks to establish a framework for evaluating ML performance and security risks across these ecosystems, forming the foundation of the Computational Performance And Security System (COMPASS) decision-support tool. The study will systematically …
Topical Text Segmentation For Stream Of Consciousness Writing, Yuwei Lu, Ryan Benton
Topical Text Segmentation For Stream Of Consciousness Writing, Yuwei Lu, Ryan Benton
Shelby Hall Graduate Research Forum Posters
Stream of consciousness writing has a long history, including novelists James Joyce and Virginia Woolf. However, there has been little work done in automated and semi-automated analysis of such writing, which is the focus of this work. We plan to divide real streams of consciousness writing into distinct topical units and then capture different momentary meaningful topics from these units. By doing this, researchers and readers could gain a more nuanced understanding of the narrative structure and thematic elements. In addition, it would also support applications in fields like psychology and linguistics, where understanding thought processes and narrative structures is …
Using Machine Learning Models To Improve The Cyber Physical Security Of Drones, Sean Lee, Aviv Segev
Using Machine Learning Models To Improve The Cyber Physical Security Of Drones, Sean Lee, Aviv Segev
Shelby Hall Graduate Research Forum Posters
This research proposes a new manner of implementing machine learning models such that, when applied on a drone, it will be able to accurately identify and maintain the authenticity of the entity sending the control data to the drone. To begin with, the drone will, for a pre-determined amount of signals received per unit time, determine the average signal strength (RSSI) of them and use that average to determine the approximate distance between the drone and the source of those signals. This single data point will be fed into a custom implementation of the SCluStream algorithm (a real-time clustering machine …
Introduction To Programming And Applied Analytics Using Python, Matt Brown
Introduction To Programming And Applied Analytics Using Python, Matt Brown
ATU Faculty OER Books and Materials
This open electronic textbook is a collection of lecture notes, assignments, and additional background material for a junior level analytics course targeted for business students, it is free to use and copy. The text assumes readers have not had prior programming or computing courses, but have had at least one analytics course. The textbook differs from other textbooks because it serves a dual purpose, to first introduce to students the Python programming language and secondly to introduce analytics programming in Python. It is not meant to be a comprehensive book on the Python language or data analytics, rather a semester’s …
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark
Poster Presentations
Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …
Providing Beginners With Interactive Exploration Of Error Messages In Clojure, John Walbran, Elena Machkasova
Providing Beginners With Interactive Exploration Of Error Messages In Clojure, John Walbran, Elena Machkasova
Undergraduate Research Symposium 2024
Programmers are imperfect, and will often make mistakes when programming and create a program error, for example, attempting to divide by zero. When a computer tries to run a program with an error, the program will halt and present the details of the error to the user in the form of an error message. These error messages are often very jargon-heavy, and are not designed to be palatable to a novice programmer. This creates significant friction for new programmers trying to learn programming languages. This work is a part of an ongoing project (called Babel) led by Elena Machkasova in …
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.
Computer Science 521 Intensive Introduction To Programming, Beth Allen
Computer Science 521 Intensive Introduction To Programming, Beth Allen
Open Educational Resources (OER)
This is a comprehensive, intensive introduction to computers, programming, data structures, abstraction, software engineering processes, and problem-solving fundamentals for learners preparing to take graduate-level courses in computer science.
The primary language used in this course is C++, with an introduction to other currently widely used languages, such as Java and Python.
Building A More Sustainable And Accessible Internet: Lightweight Web Design With Html And Css, Chelsea Thompto
Building A More Sustainable And Accessible Internet: Lightweight Web Design With Html And Css, Chelsea Thompto
Assignment Prompts
While the internet has great potential to bring people together, if the internet was a country, it would be the 7th largest energy consumer on the planet. This is set to increase in years to come moving the internet even higher on this list to become the 4th largest energy consumer if it were to be a country. So, as artists and digital citizens it is imperative that we understand how to create and display the content we produce online in ways that are sustainable and accessible.
This assignment, while slated for Art 109, may be slotted into an earlier …
Art 175 Website V1.0 Using Html5 And Css3, Gary Craig Hobbs
Art 175 Website V1.0 Using Html5 And Css3, Gary Craig Hobbs
All Assignment Prompts
No abstract provided.
Using Torchattacks To Improve The Robustness Of Models With Adversarial Training, William S. Matos Díaz
Using Torchattacks To Improve The Robustness Of Models With Adversarial Training, William S. Matos Díaz
Cybersecurity: Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment
Adversarial training has proven to be one of the most successful ways to defend models against adversarial examples. This process consists of training a model with an adversarial example to improve the robustness of the model. In this experiment, Torchattacks, a Pytorch library made for importing adversarial examples more easily, was used to determine which attack was the strongest. Later on, the strongest attack was used to train the model and make it more robust against adversarial examples. The datasets used to perform the experiments were MNIST and CIFAR-10. Both datasets were put to the test using PGD, FGSM, and …
Programming And Problem Solving I, Charity Bryan, Jennifer Purcell, Sandra Jones
Programming And Problem Solving I, Charity Bryan, Jennifer Purcell, Sandra Jones
Computer Science and Information Technology Grants Collections
This Grants Collection for Programming and Problem Solving I was created under a Round Eleven ALG Textbook Transformation Grant.
Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.
Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:
- Linked Syllabus
- Initial Proposal
- Final Report
Discrete Structures (Ksu), Rebecca H. Rutherfoord, Dawn Tatum, Susan Vandeven, Richard Halstead-Nussloch, James Rutherfoord, Zhigang Li
Discrete Structures (Ksu), Rebecca H. Rutherfoord, Dawn Tatum, Susan Vandeven, Richard Halstead-Nussloch, James Rutherfoord, Zhigang Li
Computer Science and Information Technology Grants Collections
This Grants Collection for Discrete Structures was created under a Round Eleven ALG Textbook Transformation Grant.
Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.
Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:
- Linked Syllabus
- Initial Proposal
- Final Report
Digital Cs1 Study Pack Based On Moodle And Python, Atanas Radenski
Digital Cs1 Study Pack Based On Moodle And Python, Atanas Radenski
Mathematics, Physics, and Computer Science Faculty Books and Book Chapters
We believe that CS1 courses can be made more attractive to students:
- by teaching a highly interactive scripting language – Python
- by using an open source course management system - such as Moodle - to make all course resources available in a comprehensive digital study pack, and
- by offering detailed self-guided online labs
We have used Moodle [1] and Python [2] to develop a "Python First" digital study pack [3] which comprises a wealth of new, original learning modules: extensive e-texts, detailed self-guided labs, numerous sample programs, quizzes, and slides. Our digital study pack pedagogy is described in recent ITiCSE …
Derivation Of Secure Parallel Applications By Means Of Module Embedding, Atanas Radenski
Derivation Of Secure Parallel Applications By Means Of Module Embedding, Atanas Radenski
Mathematics, Physics, and Computer Science Faculty Books and Book Chapters
An enhancement to modular languages called module embedding facilitates the development and utilization of secure generic parallel algorithms.
Is Oberon As Simple As Possible?, Atanas Radenski
Is Oberon As Simple As Possible?, Atanas Radenski
Mathematics, Physics, and Computer Science Faculty Books and Book Chapters
The design of the programming language Oberon was led by the quote by Albert Einstein: 'make it as simple as possible, but not simpler'. The objective of this paper is to analyze some design solutions and propose alternatives which could both simplify and strengthen the language without making it simpler than possible. The paper introduces one general concept, the module type, which can be used to represent records, modules, and eventually procedures. Type extension is redefined in terms of component nesting and incomplete designators. As a result, type extension supports multiple inheritance.