Computer Sciences Commons^™

A Survey On Proactive Dialogue Systems: Problems, Methods, And Prospects, Yang Deng, Wenqiang Lei, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side. It is empowered by advanced techniques to progress to more complicated tasks that require strategical and motivational interactions. In this survey, we provide a comprehensive overview of the prominent problems and advanced designs for conversational agent's proactivity in different types of dialogues. Furthermore, we discuss challenges that meet the real-world application needs but require a greater research focus in the future. We hope that …

Web Based Management System For Housing Society, Likhitha Reddy Eddala

Electronic Theses, Projects, and Dissertations

Web Based Management System for Housing Society plays a major role in our day-to-day life. We develop a global web dependent application using AngularJS, Node JS and MySQL, with Xampp as the server to make an effective management system. This system is designed to provide a user-friendly and efficient platform for managing all the details of daily notices, monthly meetings, events, payments, maids etc., This system mainly consists of three modules, they are: Admin, User and Security. Each module here serves specific features and functionalities present within society. Admin module provides the features for managing user, houses, security, maids, notices, …

Contactless Food Ordering System, Rishivar Kumar Goli

Electronic Theses, Projects, and Dissertations

Contactless food ordering has revolutionized the way a customer interacts with restaurants by allowing them to place orders and make transactions. Through these web-based platforms, customers can now browse menus, customize orders, and make payments seamlessly. By scanning the restaurant’s QR code, customers can reserve a table. If the table is available, then automatically it will be reserved. However, if the table is occupied the customer will be added to the waiting list. Once the customer selects desired food then they can securely make payments based on ordered food items. The food will be delivered straight to the customer's table. …

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

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 …

The Impact Of A Continuous Integration Service On The Delivery Time Of Merged Pull Requests, João Helis Bernardo, Daniel Alencar Da Costa, Uirá Kulesza, Christoph Treude

Research Collection School Of Computing and Information Systems

Continuous Integration (CI) is a software development practice that builds and tests software frequently (e.g., at every push). One main motivator to adopt CI is the potential to deliver software functionalities more quickly than not using CI. However, there is little empirical evidence to support that CI helps projects deliver software functionalities more quickly. Through the analysis of 162,653 pull requests (PRs) of 87 GitHub projects, we empirically study whether adopting a CI service (TRAVISCI) can quicken the time to deliver merged PRs. We complement our quantitative study by analyzing 450 survey responses from participants of 73 software projects. Our …

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 …

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

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 …

Wasm-Pbchunk: Incrementally Developing A Racket-To-Wasm Compiler Using Partial Bytecode Compilation, Adam C. Perlin

Master's Theses

Racket is a modern, general-purpose programming language with a language-oriented focus. To date, Racket has found notable uses in research and education, among other applications. To expand the reach of the language, there has been a desire to develop an efficient platform for running Racket in a web-based environment. WebAssembly (Wasm) is a binary executable format for a stack-based virtual machine designed to provide a fast, efficient, and secure execution environment for code on the web. Wasm is primarily intended to be a compiler target for higher-level languages. Providing Wasm support for the Racket project may be a promising way …

Position-Guided Text Prompt For Vision-Language Pre-Training, Alex Jinpeng Wang, Pan Zhou, Mike Zheng Shou, Yan Shuicheng

Research Collection School Of Computing and Information Systems

Vision-Language Pre-Training (VLP) has shown promising capabilities to align image and text pairs, facilitating a broad variety of cross-modal learning tasks. However, we observe that VLP models often lack the visual grounding/localization capability which is critical for many downstream tasks such as visual reasoning. In this work, we propose a novel Position-guided Text Prompt (PTP) paradigm to enhance the visual grounding ability of cross-modal models trained with VLP. Specifically, in the VLP phase, PTP divides the image into N x N blocks, and identifies the objects in each block through the widely used object detector in VLP. It then reformulates …

Transformation And Abstraction To Aid Comparison Of Binary Executables Across Compilation Environments, Jeremy D. Seideman

Dissertations, Theses, and Capstone Projects

Binary analysis allows researchers to examine how programs are constructed and how they will impact an underlying system. The various analysis techniques allow the determination of code authorship, reuse, and similarity. Detecting code reuse is significant because code reuse can be a method for vulnerabilities and security issues to spread among software projects. In this work, we examine techniques that can aid in binary analysis, especially those that abstract and transform binaries, so that they can be compared across compilation environments, including possible changes in compiler version, hardware architecture, and compilation options. Historically, this has been difficult to accomplish since …

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 …

Multi-Head Attention Graph Convolutional Network Model: End-To-End Entity And Relation Joint Extraction Based On Multi-Head Attention Graph Convolutional Network, Zhihua Tao, Chunping Ouyang, Yongbin Liu, Tonglee Chung, Yixin Cao

Research Collection School Of Computing and Information Systems

At present, the entity and relation joint extraction task has attracted more and more scholars' attention in the field of natural language processing (NLP). However, most of their methods rely on NLP tools to construct dependency trees to obtain sentence structure information. The adjacency matrix constructed by the dependency tree can convey syntactic information. Dependency trees obtained through NLP tools are too dependent on the tools and may not be very accurate in contextual semantic description. At the same time, a large amount of irrelevant information will cause redundancy. This paper presents a novel end-to-end entity and relation joint extraction …

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 …

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

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

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

Honors Program: Senior Projects (Public)

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

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

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 …

She Elicits Requirements And He Tests: Software Engineering Gender Bias In Large Language Models, Christoph Treude, Hideaki Hata

Research Collection School Of Computing and Information Systems

Implicit gender bias in software development is a well-documented issue, such as the association of technical roles with men. To address this bias, it is important to understand it in more detail. This study uses data mining techniques to investigate the extent to which 56 tasks related to software development, such as assigning GitHub issues and testing, are affected by implicit gender bias embedded in large language models. We systematically translated each task from English into a genderless language and back, and investigated the pronouns associated with each task. Based on translating each task 100 times in different permutations, we …

Boosting Just-In-Time Defect Prediction With Specific Features Of C/C++ Programming Languages In Code Changes, Chao Ni, Xiaodan Xu, Kaiwen Yang, David Lo

Research Collection School Of Computing and Information Systems

Just-in-time (JIT) defect prediction can identify changes as defect-inducing ones or clean ones and many approaches are proposed based on several programming language-independent change-level features. However, different programming languages have different characteristics and consequently may affect the quality of software projects. Meanwhile, the C programming language, one of the most popular ones, is widely used to develop foundation applications (i.e., operating system, database, compiler, etc.) in IT companies and its change-level characteristics on project quality have not been fully investigated. Additionally, whether open-source C projects have similar important features to commercial projects has not been studied much.To address the aforementioned …

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

Campus Research Month

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

Campus Research Month

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

Mathematics, Computer Science & Statistics 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

Mathematics, Computer Science & Statistics 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.

Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel

Journal of Computer Science Integration

As computer science (CS) education becomes more prevalent in K-12 instruction, it is critical for educators, researchers, and curriculum developers to identify culturally responsive and pedagogically inclusive approaches that can increase participation, access, and feelings of belonging for students from historically marginalized communities. In response, we developed an equity-centered curricular framework and illustrative crosswalk that synchronizes three distinct pedagogical approaches: culturally responsive pedagogy (CRP), Universal Design for Learning (UDL), and project-based learning (PBL). We describe the framework’s theoretical underpinnings and explain how this framework informed the development of an integrated elementary science+CS curricular unit and provide examples of its implementation. …

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 …