Programming Languages and Compilers Commons^™

Conference Report Of Why R? Turkey 2021, Mustafa Cavus, Olgun Aydin, Ozan Evkaya, Ozancan Ozdemir, Deniz Bezer, Ugur Dar

The R Journal

The Why R? Turkey 2021 as a three-day online conference was organized to bring together researchers and professionals from Turkey on April 16-17-18, 2021. We hereby aimed to promote the R community in Turkey by bringing R users with different backgrounds such as genetics, sociology, finance, economy, bio-statistics. There were 8 thematic sessions and 18 invited speakers. In this article, it is aimed to describe the preparation phase, technical details, and the impact of the conference on audience.

News From The Forwards Taskforce, Heather Turner

The R Journal

Forwards is an R Foundation taskforce working to widen the participation of underrepresented groups in the R project and in related activities, such as the useR! conference. This report rounds up activities of the taskforce during the first half of 2021.

R Foundation News, Torsten Hothorn

The R Journal

Membership fees and donations received between 2021-01-29 and 2021-07-05.

Changes In R 4.0–4.1, Tomas Kalibera, Sebastian Meyer, Kurt Hornik

The R Journal

We give a selection of the most important changes in R 4.1.0. Some statistics on source code commits and bug tracking activities are also provided.

Incorrectness Logic For Graph Programs, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Program logics typically reason about an over-approximation of program behaviour to prove the absence of bugs. Recently, program logics have been proposed that instead prove the presence of bugs by means of under-approximate reasoning, which has the promise of better scalability. In this paper, we present an under-approximate program logic for a nondeterministic graph programming language, and show how it can be used to reason deductively about program incorrectness, whether defined by the presence of forbidden graph structure or by finitely failing executions. We prove this 'incorrectness logic' to be sound and complete, and speculate on some possible future applications …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja

Publications and Research

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source …

An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja

Publications and Research

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap in knowledge of how ML systems evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source software, …

Asynchronous Validations Using Programming Contracts In Java, Rahul Shukla

Master's Projects

Design by Contract is a software development methodology based on the idea of having contracts between two software components. Programming contracts are invariants specified as pre-conditions and post-conditions. The client component must ensure that all the pre-conditions are satisfied before calling the server component. The server component must guarantee the post-conditions are met before the call returns to the client component. Current work in Design by Contract in Java focuses on writing shorthand contracts using annotations that are processed serially.

Modern software systems require a lot of business rules validations on complicated domain objects. Often, such validations are in the …

A Zenith Z-100 Emulator, Joseph Matta

Master’s Theses and Projects

The Zenith Z-100 computer was released by the Zenith Data Systems Corporation in 1982 as a competitor to the IBM PC. There are no known complete software emulations of the system. A Z-100 emulator is considered to be complete if it runs all functions of its monitor ROM BIOS program and is able to boot and run its two operating systems. One reason previous emulation attempts are not complete is that they ineffectively implement the floppy disk controller, preventing a proper transfer of the operating system from disk into memory. This project is an attempt to write a complete emulation …

City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke

Computer Science and Computer Engineering Undergraduate Honors Theses

Artificial Intelligence systems have come a long way over the years. One particular application of A.I. is its incorporation in video games. A key goal of creating an A.I. system in a video game is to convey a level of intellect to the player. During playtests for Halo: Combat Evolved, the developers at Bungie noticed that players deemed tougher enemies as more intelligent than weaker ones, despite the fact that there were no differences in behavior in the enemies. The tougher enemies provided a greater illusion of intelligence to the players. Inspired by this, I set out to create a …

Sguard: Towards Fixing Vulnerable Smart Contracts Automatically, Tai D. Nguyen, Long H. Pham, Jun Sun

Research Collection School Of Computing and Information Systems

Smart contracts are distributed, self-enforcing programs executing on top of blockchain networks. They have the potential to revolutionize many industries such as financial institutes and supply chains. However, smart contracts are subject to code-based vulnerabilities, which casts a shadow on its applications. As smart contracts are unpatchable (due to the immutability of blockchain), it is essential that smart contracts are guaranteed to be free of vulnerabilities. Unfortunately, smart contract languages such as Solidity are Turing-complete, which implies that verifying them statically is infeasible. Thus, alternative approaches must be developed to provide the guarantee. In this work, we develop an approach …

Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke

Theses/Capstones/Creative Projects

Within the United States Air Force, there are repeated patterns of differences observed during exercises. After an exercise is completed, forms are filled out detailing observations, successes, and recommendations seen throughout the exercise. At the most, no two reports are identical and must be analyzed by personnel and then categorized based on common themes observed. Developing a computer application will greatly reduce the time and resources used to analyze each After Action Report. This application can visually represent these observations and optimize the effectiveness of these exercises. The visualization is done through graphs displaying the frequency of observations and recommendations. …

Retrieval-Augmented Generation For Code Summarization Via Hybrid Gnn, Shangqing Liu, Yu Chen, Xiaofei Xie, Jingkai Siow, Yang Liu

Research Collection School Of Computing and Information Systems

Source code summarization aims to generate natural language summaries from structured code snippets for better understanding code functionalities. However, automatic code summarization is challenging due to the complexity of the source code and the language gap between the source code and natural language summaries. Most previous approaches either rely on retrieval-based (which can take advantage of similar examples seen from the retrieval database, but have low generalization performance) or generation-based methods (which have better generalization performance, but cannot take advantage of similar examples). This paper proposes a novel retrieval-augmented mechanism to combine the benefits of both worlds. Furthermore, to mitigate …

Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and shaped …

Student Academic Conference, Caitlin Brooks

Student Academic Conference

No abstract provided.

Sql Injection & Web Application Security: A Python-Based Network Traffic Detection Model, Nyki Anderson

Cybersecurity Undergraduate Research Showcase

The Internet of Things (IoT) presents a great many challenges in cybersecurity as the world grows more and more digitally dependent. Personally identifiable information (PII) (i,e., names, addresses, emails, credit card numbers) is stored in databases across websites the world over. The greatest threat to privacy, according to the Open Worldwide Application Security Project (OWASP) is SQL injection attacks (SQLIA) [1]. In these sorts of attacks, hackers use malicious statements entered into forms, search bars, and other browser input mediums to trick the web application server into divulging database assets. A proposed technique against such exploitation is convolution neural network …

Lecture 00: Opening Remarks: 46th Spring Lecture Series, Tulin Kaman

Mathematical Sciences Spring Lecture Series

Opening remarks for the 46th Annual Mathematical Sciences Spring Lecture Series at the University of Arkansas, Fayetteville.

Art 175 Website V1.0 Using Html5 And Css3, Gary Craig Hobbs

All Assignment Prompts

No abstract provided.

A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B

Journal of Applied Packaging Research

Modular packaging facilitate customization for accommodating variable product sizes in a product family. When determining package sizes for product variability, packaging engineers does not find difficulty to determine package dimension for less product variety whereas if the product variety is more, then determining the dimension of modular package involves complex decision-making and time-consuming process to find the optimal solution. This in turn directly impacts the overall lead time of the supply chain. Thus, in this paper a dynamic programming is developed to determine the quantity and dimension of modular packages for every demand of assorted products sizes. The program helps …