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Articles 31 - 60 of 991
Full-Text Articles in Programming Languages and Compilers
Machine-Learning Approach To Automated Doubt Identification On Stack Overflow Comments To Guide Programming Learners, Tianhao Chen, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo
Machine-Learning Approach To Automated Doubt Identification On Stack Overflow Comments To Guide Programming Learners, Tianhao Chen, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo
Research Collection School Of Computing and Information Systems
Stack Overflow is a popular Q&A platform for developers to find solutions to programming problems. However, due to the varying quality of user-generated answers, there is a need for ways to help users find high-quality answers. While Stack Overflow's community-based approach can be effective, important technical aspects of the answer need to be captured, and users’ comments might contain doubts regarding these aspects. In this paper, we showed the feasibility of using a machine learning model to identify doubts and conducted data analysis. We found that highly reputed users tend to raise more doubts; most answers have doubt in the …
Binalign: Alignment Padding Based Compiler Provenance Recovery, Maliha Ismail, Yan Lin, Donggyun Han, Debin Gao
Binalign: Alignment Padding Based Compiler Provenance Recovery, Maliha Ismail, Yan Lin, Donggyun Han, Debin Gao
Research Collection School Of Computing and Information Systems
Compiler provenance is significant in investigating the source-level indicators of binary code, like development-environment, source compiler, and optimization settings. Not only does compiler provenance analysis have important security applications in malware and vulnerability analysis, but it is also very challenging to extract useful artifacts from binary when high-level language constructs are missing. Previous works applied machine-learning techniques to predict the source compiler of binaries. However, most of the work is done on the binaries compiled on Linux operating system. We highlight the importance and need to explore Windows compilers and the complicated binaries compiled on the latest versions of these …
Chatgpt, Can You Generate Solutions For My Coding Exercises? An Evaluation On Its Effectiveness In An Undergraduate Java Programming Course, Eng Lieh Ouh, Benjamin Gan, Kyong Jin Shim, Swavek Wlodkowski
Chatgpt, Can You Generate Solutions For My Coding Exercises? An Evaluation On Its Effectiveness In An Undergraduate Java Programming Course, Eng Lieh Ouh, Benjamin Gan, Kyong Jin Shim, Swavek Wlodkowski
Research Collection School Of Computing and Information Systems
In this study, we assess the efficacy of employing the ChatGPT language model to generate solutions for coding exercises within an undergraduate Java programming course. ChatGPT, a large-scale, deep learning-driven natural language processing model, is capable of producing programming code based on textual input. Our evaluation involves analyzing ChatGPT-generated solutions for 80 diverse programming exercises and comparing them to the correct solutions. Our findings indicate that ChatGPT accurately generates Java programming solutions, which are characterized by high readability and well-structured organization. Additionally, the model can produce alternative, memory-efficient solutions. However, as a natural language processing model, ChatGPT struggles with coding …
Safe Mdp Planning By Learning Temporal Patterns Of Undesirable Trajectories And Averting Negative Side Effects, Siow Meng Low, Akshat Kumar, Scott Sanner
Safe Mdp Planning By Learning Temporal Patterns Of Undesirable Trajectories And Averting Negative Side Effects, Siow Meng Low, Akshat Kumar, Scott Sanner
Research Collection School Of Computing and Information Systems
In safe MDP planning, a cost function based on the current state and action is often used to specify safety aspects. In real world, often the state representation used may lack sufficient fidelity to specify such safety constraints. Operating based on an incomplete model can often produce unintended negative side effects (NSEs). To address these challenges, first, we associate safety signals with state-action trajectories (rather than just immediate state-action). This makes our safety model highly general. We also assume categorical safety labels are given for different trajectories, rather than a numerical cost function, which is harder to specify by the …
Plan-And-Solve Prompting: Improving Zero-Shot Chain-Of-Thought Reasoning By Large Language Models, Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, Ee-Peng Lim
Plan-And-Solve Prompting: Improving Zero-Shot Chain-Of-Thought Reasoning By Large Language Models, Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Large language models (LLMs) have recently been shown to deliver impressive performance in various NLP tasks. To tackle multi-step reasoning tasks, few-shot chain-of-thought (CoT) prompting includes a few manually crafted step-by-step reasoning demonstrations which enable LLMs to explicitly generate reasoning steps and improve their reasoning task accuracy. To eliminate the manual effort, Zeroshot-CoT concatenates the target problem statement with “Let’s think step by step” as an input prompt to LLMs. Despite the success of Zero-shot-CoT, it still suffers from three pitfalls: calculation errors, missing-step errors, and semantic misunderstanding errors. To address the missing-step errors, we propose Planand-Solve (PS) Prompting. It …
Deep Learning Recommendations For The Acl2 Interactive Theorem Prover, Robert K. Thompson, Robert K. Thompson
Deep Learning Recommendations For The Acl2 Interactive Theorem Prover, Robert K. Thompson, Robert K. Thompson
Master's Theses
Due to the difficulty of obtaining formal proofs, there is increasing interest in partially or completely automating proof search in interactive theorem provers. Despite being a theorem prover with an active community and plentiful corpus of 170,000+ theorems, no deep learning system currently exists to help automate theorem proving in ACL2. We have developed a machine learning system that generates recommendations to automatically complete proofs. We show that our system benefits from the copy mechanism introduced in the context of program repair. We make our system directly accessible from within ACL2 and use this interface to evaluate our system in …
Dynamic Police Patrol Scheduling With Multi-Agent Reinforcement Learning, Songhan Wong, Waldy Joe, Hoong Chuin Lau
Dynamic Police Patrol Scheduling With Multi-Agent Reinforcement Learning, Songhan Wong, Waldy Joe, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Effective police patrol scheduling is essential in projecting police presence and ensuring readiness in responding to unexpected events in urban environments. However, scheduling patrols can be a challenging task as it requires balancing between two conflicting objectives namely projecting presence (proactive patrol) and incident response (reactive patrol). This task is made even more challenging with the fact that patrol schedules do not remain static as occurrences of dynamic incidents can disrupt the existing schedules. In this paper, we propose a solution to this problem using Multi-Agent Reinforcement Learning (MARL) to address the Dynamic Bi-objective Police Patrol Dispatching and Rescheduling Problem …
Mapping Programs To Equations, Hessamaldin Mohammadi
Mapping Programs To Equations, Hessamaldin Mohammadi
Dissertations
Extracting the function of a program from a static analysis of its source code is a valuable capability in software engineering; at a time when there is increasing talk of using AI (Artificial Intelligence) to generate software from natural language specifications, it becomes increasingly important to determine the exact function of software as written, to figure out what AI has understood the natural language specification to mean. For all its criticality, the ability to derive the domain-to-range function of a program has proved to be an elusive goal, due primarily to the difficulty of deriving the function of iterative statements. …
Visualized Algorithm Engineering On Two Graph Partitioning Problems, Zizhen Chen
Visualized Algorithm Engineering On Two Graph Partitioning Problems, Zizhen Chen
Computer Science and Engineering Theses and Dissertations
Concepts of graph theory are frequently used by computer scientists as abstractions when modeling a problem. Partitioning a graph (or a network) into smaller parts is one of the fundamental algorithmic operations that plays a key role in classifying and clustering. Since the early 1970s, graph partitioning rapidly expanded for applications in wide areas. It applies in both engineering applications, as well as research. Current technology generates massive data (“Big Data”) from business interactions and social exchanges, so high-performance algorithms of partitioning graphs are a critical need.
This dissertation presents engineering models for two graph partitioning problems arising from completely …
Utilizing Machine Learning Techniques To Predict Credit Card Payment Defaults, Madison Guerra
Utilizing Machine Learning Techniques To Predict Credit Card Payment Defaults, Madison Guerra
Theses and Dissertations
The question of accurately predicting credit card defaulters has been explored in numerous studies in the past. In these studies, the researchers utilized various machine learning theories and techniques to make the determination the extent of defaults. Unfortunately, some constraints were encountered, and the limitations that existed from the previous works have been discussed. This project attempted to address these issues with special attention given to more recently available data. Specifically, in this project, we looked at data provided by one Kaggle user, which utilized the data from the American Express credit card competition, which ranges from late March 2018 …
Designing Programming Languages For Writing Maintainable Software, Aaron Friesen
Designing Programming Languages For Writing Maintainable Software, Aaron Friesen
Honors Theses
Maintainability is crucial to the long-term success of software projects. Among other factors, it is affected by the programming language in which the software is written. Programming language designers should be conscious of how their design decisions can influence software maintainability. Non-functional properties of a language can affect the readability of source code in ways beyond the control of programmers. Language features can cause or prevent certain classes of bugs, and runtime issues especially can require significant maintenance effort. Tools external to the language, especially those developed and distributed by language implementers, can aid in the creation of maintainable software. …
Identifying And Analyzing Multi-Star Systems Among Tess Planetary Candidates Using Gaia, Katie E. Bailey
Identifying And Analyzing Multi-Star Systems Among Tess Planetary Candidates Using Gaia, Katie E. Bailey
Electronic Theses and Dissertations
Exoplanets represent a young, rapidly advancing subfield of astrophysics where much is still unknown. It is therefore important to analyze trends among their parameters to learn more about these systems. More complexity is added to these systems with the presence of additional stellar companions. To study these complex systems, one can employ programming languages such as Python to parse databases such as those constructed by TESS and Gaia to bridge the gap between exoplanets and stellar companions. Data can then be analyzed for trends in these multi-star exoplanet systems and in juxtaposition to their single-star counterparts. This research was able …
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Honors Scholar Theses
Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …
Dynamically Finding Optimal Kernel Launch Parameters For Cuda Programs, Taabish Jeshani
Dynamically Finding Optimal Kernel Launch Parameters For Cuda Programs, Taabish Jeshani
Electronic Thesis and Dissertation Repository
In this thesis, we present KLARAPTOR (Kernel LAunch parameters RAtional Program estimaTOR), a freely available tool to dynamically determine the values of kernel launch parameters of a CUDA kernel. We describe a technique for building a helper program, at the compile-time of a CUDA program, that is used at run-time to determine near-optimal kernel launch parameters for the kernels of that CUDA program. This technique leverages the MWP-CWP performance prediction model, runtime data parameters, and runtime hardware parameters to dynamically determine the launch parameters for each kernel invocation. This technique is implemented within the KLARAPTOR tool, utilizing the LLVM Pass …
Code Generation Based On Inference And Controlled Natural Language Input, Howard R. Dittmer
Code Generation Based On Inference And Controlled Natural Language Input, Howard R. Dittmer
College of Computing and Digital Media Dissertations
Over time the level of abstraction embodied in programming languages has continued to grow. Paradoxically, most programming languages still require programmers to conform to the language's rigid constructs. These constructs have been implemented in the name of efficiency for the computer. However, the continual increase in computing power allows us to consider techniques not so limited. To this end, we have created CABERNET, a Controlled Natural Language (CNL) based approach to program creation. CABERNET allows programmers to use a simple outline-based syntax. This syntax enables increased programmer efficiency.
CNLs have previously been used to document requirements. We have taken this …
Web Repository Of Southern’S Research Projects, Rebecca Zaldivar, Siegwart Mayr
Web Repository Of Southern’S Research Projects, Rebecca Zaldivar, Siegwart Mayr
Campus Research Day
A research repository was created so that Southern Adventist University has a central place for all past, current, and future research projects. This repository is a web application created with the use of the Yii framework that utilizes PHP and SQL. The repository has a user-friendly interface to let authorized users upload the information about their projects. Also, professors and students from different departments can see the list of projects per department.
Game-Based Learning Activities And Assignments, Samuel Rivera, Siegwart Mayr
Game-Based Learning Activities And Assignments, Samuel Rivera, Siegwart Mayr
Campus Research Day
The Center for Innovation and Research in Computing (CIRC) is creating a web application that uses game-based learning to help students be engaged and collaborate, as an adventure-based quest.
In this research project, the activity module was created for this web application. This module contains assignment creation, completion, and grading. These assignments can be included in the quests and courses. The seamless connection between the activity module and the course module was possible with the Yii framework.
R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame
R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame
Mathematics and Computer Science Presentations
Text mining and text analysis is a way of understanding text documents using r coding that is more frequently used for numbered data. It helps with understanding portions of the text and drawing conclusions from there. This research looks specifically at the Adam Smith required documents that are used in the CIE course designated for freshmen. It looks at sentiments of the documents, including word sentiment, sentence sentiment, page and overall document sentiment as well. It provides visuals of word clouds to portray word frequency, tf-idf (which is explained in the presentation) and bigram analysis.
Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe
Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe
Mathematics and Computer Science Presentations
Our STAT-451 class has worked with analyzing the words from CIE texts and assigning them to a sentiment or feeling and comparing them with one another using RStudio. This project analyzes texts from three sources: The Narrative of the Life of Frederick Douglass, The Declaration of Independence and the Declaration of Sentiments.
A Graphical User Interface Using Spatiotemporal Interpolation To Determine Fine Particulate Matter Values In The United States, Kelly M. Entrekin
A Graphical User Interface Using Spatiotemporal Interpolation To Determine Fine Particulate Matter Values In The United States, Kelly M. Entrekin
Honors College Theses
Fine particulate matter or PM2.5 can be described as a pollution particle that has a diameter of 2.5 micrometers or smaller. These pollution particle values are measured by monitoring sites installed across the United States throughout the year. While these values are helpful, a lot of areas are not accounted for as scientists are not able to measure all of the United States. Some of these unmeasured regions could be reaching high PM2.5 values over time without being aware of it. These high values can be dangerous by causing or worsening health conditions, such as cardiovascular and lung diseases. Within …
Code Will Tell: Visual Identification Of Ponzi Schemes On Ethereum, Xiaolin Wen, Kim Siang Yeo, Yong Wang, Ling Cheng, Feida Zhu, Min Zhu
Code Will Tell: Visual Identification Of Ponzi Schemes On Ethereum, Xiaolin Wen, Kim Siang Yeo, Yong Wang, Ling Cheng, Feida Zhu, Min Zhu
Research Collection School Of Computing and Information Systems
Ethereum has become a popular blockchain with smart contracts for investors nowadays. Due to the decentralization and anonymity of Ethereum, Ponzi schemes have been easily deployed and caused significant losses to investors. However, there are still no explainable and effective methods to help investors easily identify Ponzi schemes and validate whether a smart contract is actually a Ponzi scheme. To fill the research gap, we propose PonziLens, a novel visualization approach to help investors achieve early identification of Ponzi schemes by investigating the operation codes of smart contracts. Specifically, we conduct symbolic execution of opcode and extract the control flow …
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Library Philosophy and Practice (e-journal)
Abstract
Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …
Large-Scale Identification And Analysis Of Factors Impacting Simple Bug Resolution Times In Open Source Software Repositories, Elia Eiroa-Lledo, Rao Hamza Ali, Gabriela Pinto, Jillian Anderson, Erik Linstead
Large-Scale Identification And Analysis Of Factors Impacting Simple Bug Resolution Times In Open Source Software Repositories, Elia Eiroa-Lledo, Rao Hamza Ali, Gabriela Pinto, Jillian Anderson, Erik Linstead
Engineering Faculty Articles and Research
One of the most prominent issues the ever-growing open-source software community faces is the abundance of buggy code. Well-established version control systems and repository hosting services such as GitHub and Maven provide a checks-and-balances structure to minimize the amount of buggy code introduced. Although these platforms are effective in mitigating the problem, it still remains. To further the efforts toward a more effective and quicker response to bugs, we must understand the factors that affect the time it takes to fix one. We apply a custom traversal algorithm to commits made for open source repositories to determine when “simple stupid …
Contrastive Learning Approach To Word-In-Context Task For Low-Resource Languages, Pei-Chi Lo, Yang-Yin Lee, Hsien-Hao Chen, Agus Trisnajaya Kwee, Ee-Peng Lim
Contrastive Learning Approach To Word-In-Context Task For Low-Resource Languages, Pei-Chi Lo, Yang-Yin Lee, Hsien-Hao Chen, Agus Trisnajaya Kwee, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Word in context (WiC) task aims to determine whether a target word’s occurrences in two sentences share the same sense. In this paper, we propose a Contrastive Learning WiC (CLWiC) framework to improve the learning of sentence/word representations and classification of target word senses in the sentence pair when performing WiC on lowresource languages. In representation learning, CLWiC trains a pre-trained language model’s ability to cope with lowresource languages using both unsupervised and supervised contrastive learning. The WiC classifier learning further finetunes the language model with WiC classification loss under two classifier architecture options, SGBERT and WiSBERT, which use single-encoder …
Csc 71010/Csci 77100: Programming Languages/Software Engineering, Raffi T. Khatchadourian
Csc 71010/Csci 77100: Programming Languages/Software Engineering, Raffi T. Khatchadourian
Open Educational Resources
No abstract provided.
Introduction, Raffi T. Khatchadourian
Introduction, Raffi T. Khatchadourian
Open Educational Resources
No abstract provided.
Reengineering And Refactoring, Raffi T. Khatchadourian
Reengineering And Refactoring, Raffi T. Khatchadourian
Open Educational Resources
No abstract provided.
Wala Quick Start, Raffi T. Khatchadourian
Wala Quick Start, Raffi T. Khatchadourian
Open Educational Resources
Setting up and trying the TJ Watson Library for Analysis (WALA).
Building An Ast Eclipse Plug-In, Raffi T. Khatchadourian
Building An Ast Eclipse Plug-In, Raffi T. Khatchadourian
Open Educational Resources
Complete the Building an AST Eclipse Plug-in assignment. Once it works, find a medium-sized open-source Java project to run your plugin on. You may want to explore GitHub. Import the project into Eclipse and run your plug-in on it. Report on the following, which may require you to change some of the source code so that it is convenient:
- Project name.
- Project URL.
- Project description.
- The number of classes in the project.
- The number of user-defined methods in the project.
- For each class, the number of method calls.
- Statistics about the method calls:
- The total number of method calls …
Working With Control-Flow Graphs, Raffi T. Khatchadourian
Working With Control-Flow Graphs, Raffi T. Khatchadourian
Open Educational Resources
No abstract provided.