Supporting Software Engineers With Large Language Model-Based Automation,
2023
Singapore Management University
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), …
Towards Securing Smart Contracts Systematically,
2023
Singapore Management University
Towards Securing Smart Contracts Systematically, Duy Tai Nguyen
Dissertations and Theses Collection (Open Access)
Smart contracts are a groundbreaking technique that allows users to programmatically modify the state of the blockchain. They are essentially self-enforcing programs that are deployed and executed on top of the blockchain. In recent years, we have witnessed various smart contract incidents that led to substantial financial losses and even business closures. These incidents mainly arise from design flaws in Solidity, a dominant programming language for writing smart contracts, which complicates the process of detecting and repairing vulnerabilities. Furthermore, there is a growing interest in attacking smart contracts by the attackers. This thesis is dedicated to developing effective methods to …
On The Usage Of Continual Learning For Out-Of-Distribution Generalization In Pre-Trained Language Models Of Code,
2023
Singapore Management University
On The Usage Of Continual Learning For Out-Of-Distribution Generalization In Pre-Trained Language Models Of Code, Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari A. Sahraoui
Research Collection School Of Computing and Information Systems
Pre-trained language models (PLMs) have become a prevalent technique in deep learning for code, utilizing a two-stage pre-training and fine-tuning procedure to acquire general knowledge about code and specialize in a variety of downstream tasks. However, the dynamic nature of software codebases poses a challenge to the effectiveness and robustness of PLMs. In particular, world-realistic scenarios potentially lead to significant differences between the distribution of the pre-training and test data, i.e., distribution shift, resulting in a degradation of the PLM's performance on downstream tasks. In this paper, we stress the need for adapting PLMs of code to software data whose …
C³: Code Clone-Based Identification Of Duplicated Components,
2023
Singapore Management University
C³: Code Clone-Based Identification Of Duplicated Components, Yanming Yang, Ying Zou, Xing Hu, David Lo, Chao Ni, John C. Grundy, Xin: Xia
Research Collection School Of Computing and Information Systems
Reinventing the wheel is a detrimental programming practice in software development that frequently results in the introduction of duplicated components. This practice not only leads to increased maintenance and labor costs but also poses a higher risk of propagating bugs throughout the system. Despite numerous issues introduced by duplicated components in software, the identification of component-level clones remains a significant challenge that existing studies struggle to effectively tackle. Specifically, existing methods face two primary limitations that are challenging to overcome: 1) Measuring the similarity between different components presents a challenge due to the significant size differences among them; 2) Identifying …
Class Participation: Using Technology To Enhance Efficiency And Fairness,
2023
Singapore Management University
Class Participation: Using Technology To Enhance Efficiency And Fairness, Benjamin Gan, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
Class participation can be considered as contribution to discussion, attendance, presentations, unsolicited responses, questions, comments, etc. What counts may vary across individual teachers. The more students participate, the less memorization they do, and the more they engage in higher levels of thinking, including interpretation, analysis, and synthesis. However, only a handful of students in many classrooms participate regularly, a phenomenon dubbed as "consolidation of responsibility". This study provides a literature review of inclass participation, as well as pedagogies and technologies that enhance participation. Pedagogies such as active learning, group learning, project-based learning and flipped classroom. Technologies to automate attendance taking, …
Do Contributing Files Provide Information About Oss Newcomers' Onboarding Barriers?,
2023
Singapore Management University
Do Contributing Files Provide Information About Oss Newcomers' Onboarding Barriers?, Felipe Fronchetti, David Shepherd, Igor Wiese, Christoph Treude, Marco Gerosa, Igor Steinmacher
Research Collection School Of Computing and Information Systems
Effectively onboarding newcomers is essential for the success of open source projects. These projects often provide onboarding guidelines in their ‘CONTRIBUTING’ files (e.g., CONTRIBUTING.md on GitHub). These files explain, for example, how to find open tasks, implement solutions, and submit code for review. However, these files often do not follow a standard structure, can be too large, and miss barriers commonly found by newcomers. In this paper, we propose an automated approach to parse these CONTRIBUTING files and assess how they address onboarding barriers. We manually classified a sample of files according to a model of onboarding barriers from the …
Robust Test Selection For Deep Neural Networks,
2023
Chongqing University
Robust Test Selection For Deep Neural Networks, Weifeng Sun, Meng Yan, Zhongxin Liu, David Lo
Research Collection School Of Computing and Information Systems
Deep Neural Networks (DNNs) have been widely used in various domains, such as computer vision and software engineering. Although many DNNs have been deployed to assist various tasks in the real world, similar to traditional software, they also suffer from defects that may lead to severe outcomes. DNN testing is one of the most widely used methods to ensure the quality of DNNs. Such method needs rich test inputs with oracle information (expected output) to reveal the incorrect behaviors of a DNN model. However, manually labeling all the collected test inputs is a labor-intensive task, which delays the quality assurance …
Exgen: Ready-To-Use Exercise Generation In Introductory Programming Courses,
2023
Singapore Management University
Exgen: Ready-To-Use Exercise Generation In Introductory Programming Courses, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna
Research Collection School Of Computing and Information Systems
In introductory programming courses, students as novice programmers would benefit from doing frequent practices set at a difficulty level and concept suitable for their skills and knowledge. However, setting many good programming exercises for individual learners is very time-consuming for instructors. In this work, we propose an automated exercise generation system, named ExGen, which leverages recent advances in pre-trained large language models (LLMs) to automatically create customized and ready-to-use programming exercises for individual students ondemand. The system integrates seamlessly with Visual Studio Code, a popular development environment for computing students and software engineers. ExGen effectively does the following: 1) maintaining …
Software Architecture In Practice: Challenges And Opportunities,
2023
Singapore Management University
Software Architecture In Practice: Challenges And Opportunities, Zhiyuan Wan, Yun Zhang, Xin Xia, Yi Jiang, David Lo
Research Collection School Of Computing and Information Systems
Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice. Despite past efforts, we have little understanding of how practitioners perform software architecture related activities, and what challenges they face. Through interviews with 32 practitioners from 21 organizations across three continents, we identified challenges that practitioners face in software architecture practice during software development and maintenance. We reported on common software architecture activities at software requirements, design, construction and testing, and maintenance stages, as well as corresponding …
How Helpful Do Novice Programmers Find The Feedback Of An Automated Repair Tool?,
2023
Singapore Management University
How Helpful Do Novice Programmers Find The Feedback Of An Automated Repair Tool?, Oka Kurniawan, Christopher M. Poskitt, Ismam Al Hoque, Norman Tiong Seng Lee, Cyrille Jégourel, Nachamma Sockalingam
Research Collection School Of Computing and Information Systems
Immediate feedback has been shown to improve student learning. In programming courses, immediate, automated feedback is typically provided in the form of pre-defined test cases run by a submission platform. While these are excellent for highlighting the presence of logical errors, they do not provide novice programmers enough scaffolding to help them identify where an error is or how to fix it. To address this, several tools have been developed that provide richer feedback in the form of program repairs. Studies of such tools, however, tend to focus more on whether correct repairs can be generated, rather than how novices …
A Closer Look At The Security Risks In The Rust Ecosystem,
2023
Singapore Management University
A Closer Look At The Security Risks In The Rust Ecosystem, Xiaoye Zheng, Zhiyuan Wan, Yun Zhang, Rui Chang, David Lo
Research Collection School Of Computing and Information Systems
Rust is an emerging programming language designed for the development of systems software. To facilitate the reuse of Rust code, crates.io, as a central package registry of the Rust ecosystem, hosts thousands of third-party Rust packages. The openness of crates.io enables the growth of the Rust ecosystem but comes with security risks by severe security advisories. Although Rust guarantees a software program to be safe via programming language features and strict compile-time checking, the unsafe keyword in Rust allows developers to bypass compiler safety checks for certain regions of code. Prior studies empirically investigate the memory safety and concurrency bugs …
Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model,
2023
United Arab Emirates University
Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei
Thesis/ Dissertation Defenses
The dress code violation detection system is crucial for assessing clothing appropriateness in public areas. This study aims to improve this system using advanced computer vision and machine learning techniques to more effectively categorize people's attire in images and videos. To enhance adaptability and create a user-friendly graphical interface for system management and deployment, we have generated a unique dataset from various contexts mix of Western and Arabic clothing. This allows users to interact with graphical components, including the ability to upload images or use live video for clothing detection. Moreover, we have taken privacy concerns into account and implemented …
A Data-Efficient Approach For Effective Diagnosis Of Left Ventricular Hypertrophy From Echocardiography Modality,
2023
United Arab Emirates University
A Data-Efficient Approach For Effective Diagnosis Of Left Ventricular Hypertrophy From Echocardiography Modality, Moomal Farhad Farhad
Thesis/ Dissertation Defenses
Left Ventricular Hypertrophy (LVH) is a medical condition characterized by the thickening and enlargement of the left ventricle (LV) of the heart. Accurate and timely diagnosis of LVH is vital for clinical prognosis and treatment decisions. Echocardiography has emerged as the gold standard for diagnosing LVH due to its ability to independently predict long-term risks such as heart failure and stroke. Echocardiography, a non-invasive and cost-effective imaging technology, is instrumental in assessing various aspects of heart health. Among the critical diagnostic calculations made possible by echocardiography, the determination of ejection fraction and heart chamber size is paramount in assessing LVH. …
Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement,
2023
United Arab Emirates University
Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement, Souheil Abdel-Latif Akacha
Thesis/ Dissertation Defenses
The rapid adoption of Learning Management Systems (LMSs) like Moodle, Chamilo, and Ilias became essential for online education due to the COVID-19 pandemic. While this transformation revolutionized online learning, it also exposed security vulnerabilities that require immediate attention. This thesis explores these security concerns within widely used LMSs, namely Moodle, Chamilo, and Ilias, across pre-pandemic, pandemic, and post-pandemic periods. By analyzing existing patches and security measures and considering emerging cybersecurity technologies and trends, comprehensive recommendations are formulated to enhance the security and sustainability of LMSs against evolving cyber threats, offering valuable insights to educational institutions for proactive risk mitigation. Therefore, …
Effective And Efficient Semantic Representations And Their Applications,
2023
Singapore Management University
Effective And Efficient Semantic Representations And Their Applications, Chong Cher Chia
Dissertations and Theses Collection (Open Access)
The proliferation of affordable and compact digital storage has also led to the creation of enormous databases of information, and much attention has been focused on the problem of processing unorganized and unstructured information into some form from which additional value can be extracted. Contemporary approaches to this problem virtually necessitate the use of complex models running on computational systems due to the sheer volume of information to be processed. While it is possible for the model to be fed the actual data as input, typically a representation of the data is used instead. These representations are therefore of interest, …
Optimizing E-Payment Applications For Older Adults: User-Centered Solutions To Improve Security, Privacy, Usability, And Accessibility,
2023
University of Denver
Optimizing E-Payment Applications For Older Adults: User-Centered Solutions To Improve Security, Privacy, Usability, And Accessibility, Urvashi Kishnani
Electronic Theses and Dissertations
In an increasingly digital world, older adults are rapidly becoming a vital demographic in the realm of electronic financial transactions. It is imperative to address their unique needs and challenges to ensure their financial well-being. Older adults can be more vulnerable to various online threats, making security and privacy paramount. As they adapt to the digital age, understanding their specific privacy concerns and preferences is crucial for creating trustworthy e-payment systems. Moreover, enhancing the usability of e-payment applications for older adults promotes financial independence and inclusion, contributing to their overall quality of life. By focusing on these critical dimensions, we …
Hiking Trail Generation In Infinite Landscapes,
2023
Southern Adventist University
Hiking Trail Generation In Infinite Landscapes, Matthew Jensen
MS in Computer Science Project Reports
This project procedurally generates an infinite wilderness populated with deterministic hiking trails. Our approach recognizes that hiking trails depend on contextual information beyond the location of the path itself. To address this, we implemented a layered procedural system that orchestrates the generation process. This helps ensure the availability of contextual data at each stage. The first layer handles terrain generation, establishing the foundational landscape upon which trails will traverse. Subsequent layers handle point of interest identification and selection, trail network optimization through proximity graphs, and efficient pathfinding across the terrain. A notable feature of our approach is the deterministic nature …
Intelligent Computation Offloading In Edge And Cloud Internet Of Vehicles System,
2023
United Arab Emirates University
Intelligent Computation Offloading In Edge And Cloud Internet Of Vehicles System, Huned Yusufbhai Materwala
Dissertations
The emergence of Internet of Vehicles technology through Vehicular Ad-hoc Networks represents a promising development in the realm of smart city. It empowers the development of smart city applications with a primary focus on improving traffic safety, optimizing traffic flow, and enhancing the overall driving experience. These applications come with demanding quality of service requirements outlined in Service Level Agreements (SLAs). They are communication-intensive, requiring a real-time response, and computation-intensive, demanding high processing. Due to inherent limitations in the computational and storage capacities of vehicles, the system relies on offloading application requests to edge and cloud computing infrastructures. However, the …
Turn-It-Up: Rendering Resistance For Knobs In Virtual Reality Through Undetectable Pseudo-Haptics,
2023
Universitat des Saarlandes
Turn-It-Up: Rendering Resistance For Knobs In Virtual Reality Through Undetectable Pseudo-Haptics, Martin Feick, Andre Zenner, Oscar Ariza, Anthony Tang, Cihan Biyikli, Antonio Kruger
Research Collection School Of Computing and Information Systems
Rendering haptic feedback for interactions with virtual objects is an essential part of effective virtual reality experiences. In this work, we explore providing haptic feedback for rotational manipulations, e.g., through knobs. We propose the use of a Pseudo-Haptic technique alongside a physical proxy knob to simulate various physical resistances. In a psychophysical experiment with 20 participants, we found that designers can introduce unnoticeable offsets between real and virtual rotations of the knob, and we report the corresponding detection thresholds. Based on these, we present the Pseudo-Haptic Resistance technique to convey physical resistance while applying only unnoticeable pseudo-haptic manipulation. Additionally, we …
An Idealist’S Approach For Smart Contract Correctness,
2023
Singapore Management University
An Idealist’S Approach For Smart Contract Correctness, Duy Tai Nguyen, Hong Long Pham, Jun Sun, Quang Loc Le
Research Collection School Of Computing and Information Systems
In this work, we experiment an idealistic approach for smart contract correctness verification and enforcement, based on the assumption that developers are either desired or required to provide a correctness specification due to the importance of smart contracts and the fact that they are immutable after deployment. We design a static verification system with a specification language which supports fully compositional verification (with the help of function specifications, contract invariants, loop invariants and call invariants). Our approach has been implemented in a tool named iContract which automatically proves the correctness of a smart contract statically or checks the unverified part …
