Software Engineering Commons^™

Chatbot4qr: Interactive Query Refinement For Technical Question Retrieval, Neng Zhang, Qiao Huang, Xin Xia, Ying Zou, David Lo, Zhenchang Xing

Research Collection School Of Computing and Information Systems

Technical Q&A sites (e.g., Stack Overflow(SO)) are important resources for developers to search for knowledge about technical problems. Search engines provided in Q&A sites and information retrieval approaches have limited capabilities to retrieve relevant questions when queries are imprecisely specified, such as missing important technical details (e.g., the user's preferred programming languages). Although many automatic query expansion approaches have been proposed to improve the quality of queries by expanding queries with relevant terms, the information missed is not identified. Moreover, without user involvement, the existing query expansion approaches may introduce unexpected terms and lead to undesired results. In this paper, …

Interactive Sc Historical Map Application By Capistonsker, Joseph Cammarata, James Davis, Matt Duggan, Lauren Hodges, Ian Urton

Senior Theses

The Interactive SC Historical Map Application by CapiStonsker, hereby known as CapiStonsker, is an android application that creates a comprehensive user experience for individuals and groups to engage with their local Columbia history. Users of this application can discover local historical landmarks by scrolling through the interactive map on the home screen, searching for markers by name using the search bar, filtering by county, or scrolling through a list of markers sorted by proximity. If a marker catches a user's attention, he or she can tap it to learn more information, get directions, or save it for later by adding …

Comai: Enabling Lightweight, Collaborative Intelligence By Retrofitting Vision Dnns, Kasthuri Jayarajah, Dhanuja Wanniarachchige, Tarek Abdelzaher, Archan Misra

Research Collection School Of Computing and Information Systems

While Deep Neural Network (DNN) models have transformed machine vision capabilities, their extremely high computational complexity and model sizes present a formidable deployment roadblock for AIoT applications. We show that the complexity-vs-accuracy-vs-communication tradeoffs for such DNN models can be significantly addressed via a novel, lightweight form of “collaborative machine intelligence” that requires only runtime changes to the inference process. In our proposed approach, called ComAI, the DNN pipelines of different vision sensors share intermediate processing state with one another, effectively providing hints about objects located within their mutually-overlapping Field-of-Views (FoVs). CoMAI uses two novel techniques: (a) a secondary shallow ML …

Data Source Selection In Federated Learning: A Submodular Optimization Approach, Ruisheng Zhang, Yansheng Wang, Zimu Zhou, Ziyao Ren, Yongxin Tong, Ke Xu

Research Collection School Of Computing and Information Systems

Federated learning is a new learning paradigm that jointly trains a model from multiple data sources without sharing raw data. For the practical deployment of federated learning, data source selection is compulsory due to the limited communication cost and budget in real-world applications. The necessity of data source selection is further amplified in presence of data heterogeneity among clients. Prior solutions are either low in efficiency with exponential time cost or lack theoretical guarantees. Inspired by the diminishing marginal accuracy phenomenon in federated learning, we study the problem from the perspective of submodular optimization. In this paper, we aim at …

Performance Analysis And Improvement For Scalable And Distributed Applications Based On Asynchronous Many-Task Systems, Nanmiao Wu

LSU Doctoral Dissertations

As the complexity of recent and future large-scale data and exascale systems architectures grows, so do productivity, portability, software scalability, and efficient utilization of system resources challenges presented to both industry and the research community. Software solutions and applications are expected to scale in performance on such complex systems. Asynchronous many-task (AMT) systems, taking advantage of multi-core architectures with light-weight threads, asynchronous executions, and smart scheduling, are showing promise in addressing these challenges.

In this research, we implement several scalable and distributed applications based on HPX, an exemplar AMT runtime system. First, a distributed HPX implementation for a parameterized benchmark …

Backup Automation Using Power Automate For Malaysian Vaccination Centres, Raadhesh Kannan, Chin Ji Jian

Journal of Informatics and Web Engineering

The Covid-19 pandemic has tested the world, especially the vaccine centres when it comes to logistics, maintenance of records, and issuing of vaccination certifications. The Malaysian vaccination centres (PPVs) known as Pusat Pemberian Vaksin in Malaysia have a secure, and reliable system to maintain records of who has been vaccinated and when. No system is fully secure and reliable, thus there needs to be a backup if anything happens to the records like data loss or tampering of records. Although the information flow is simplified using the MySejahtera app and scanning of QR codes, there is no contingency prepared should …

Localization Techniques Overview Towards 6g Communication, Nawaid Hasan, Azlan Abd Aziz, Azwan Mahmud, Nur Asyiqin Binte Hamzah, Noor Ziela Abd Rahman

Journal of Informatics and Web Engineering

Worldwide Researchers and scientist have started the investigation of the sixth generation (6G) while the fifth generation (5G) cellular system is being deployed. Under this main investigation the main aim of 6G is to provide intelligent and ubiquitous wireless connectivity with Terabits per second (Tbps) data rates. Accurate location information of the mobile devices is very much useful to accomplish these aims with the improvements of various parameters of wireless communication. The development in communication technology often creates new opportunities to improve the localization efficiency as demonstrated by the expected centimetre-level localization accuracy in 6G. While there are comprehensive literatures …

Performance Of Sentiment Classification On Tweets Of Clothing Brands, Muhammad Shafiq Jalani, Hu Ng, Timothy Tzen Vun Yap, Vik Tor Goh

Journal of Informatics and Web Engineering

Social media such as Facebook, Instagram, LinkedIn, and Twitter ease the sharing of ideas, thoughts, videos, and photos and information through the building of virtual networks and communities. This has allowed companies and products to reach a wider audience in terms of marketing and advertising, and to gauge feedback from the public. This research investigates clothing brand mentions on Twitter to perform sentiment analysis on users’ thoughts on three clothing brands, namely Asos, Uniqlo and Topshop. The data is collected by applying python libraries, Tweepy to access data from the Twitter streaming API. Following that, data pre-processing such as tokenization, …

Incorporating Semi-Automated Approach For Effective Software Requirements Prioritization: A Framework Design, Fang-Fang Chua, Tek-Yong Lim, Bushra Tajuddin, Amarilis Putri Yanuarifiani

Journal of Informatics and Web Engineering

Software Requirements Prioritization (SRP) is one of the crucial processes in software requirements engineering. It presents a challenging task to decide among the pool of requirements and the variance of the stakeholder’s needs in prioritizing requirements. Semi-automated requirements prioritization is implemented in both manual and automatic processes. When prioritizing requirements, these aspects such as importance, time, cost and risk, should be taken into account. The emergence of machine learning is advancing to improve and automate the SRP process whereby decision making can be performed with minimal human intervention. Incorporating machine learning approaches in prioritization techniques can be implemented in the …

The Impacts Of The Use Of Thematic & Chronologic Multi-Modal Information Representation On Sequential And Global Students’ Historical Understanding, Ling Weay Ang, Sellappan Palaniappan

Journal of Informatics and Web Engineering

This study examined the two different modes of multi-modes information presentations that affected sequential and global learners' history understanding: thematic and chronological. A total of 134 secondary schools’ students were enrolled (69 learning in chronological mode, 65 learning in thematic mode). Before the start of the treatment session, students were given a pre-test. The results showed that multimodal information presentation did not have a significantly great impact on historical learning or between pupils who learn in chronological and thematic ways. The chronological frame of reference technique, which reflected an interactive timeline, was reported to have supported students' sequential learning in …

The Impact Of Dynamic Difficulty Adjustment On Player Experience In Video Games, Chineng Vang

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Dynamic Difficulty Adjustment (DDA) is a process by which a video game adjusts its level of challenge to match a player’s skill level. Its popularity in the video game industry continues to grow as it has the ability to keep players continuously engaged in a game, a concept referred to as Flow. However, the influence of DDA on games has received mixed responses, specifically that it can enhance player experience as well as hinder it. This paper explores DDA through the Monte Carlo Tree Search algorithm and Reinforcement Learning, gathering feedback from players seeking to understand what about DDA is …

Design And Development Of Software With A Graphical User Interface To Display And Convert Multiple Microscopic Histology Images, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Histological images are widely used to assess the microscopic anatomy of biological tissues. Recent advancements in image analysis allow the identification of structural features on histological sections that can help advance medical device development, brain and cancer research, drug discovery, vascular mechanobiology, and many other fields. Histological slide scanners create images in SVS and TIFF formats that were designed to archive image blocks and high-resolution textual information. Because these formats were primarily intended for storage, they are often not compatible with conventional image analysis software and require conversion before they can be used in research. We have developed a user-friendly …

Digital Discrimination In The Sharing Economy: Evidence, Policy, And Feature Analysis, Miroslav Tushev

LSU Doctoral Dissertations

Applications (apps) of the Digital Sharing Economy (DSE), such as Uber, Airbnb, and TaskRabbit, have become a main facilitator of economic growth and shared prosperity in modern-day societies. However, recent research has revealed that the participation of minority groups in DSE activities is often hindered by different forms of bias and discrimination. Evidence of such behavior has been documented across almost all domains of DSE, including ridesharing, lodging, and freelancing. However, little is known about the under- lying design decisions of DSE systems which allow certain demographics of the market to gain unfair advantage over others. To bridge this knowledge …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

Improving Adversarial Attacks Against Malconv, Justin Burr

Masters Theses & Doctoral Dissertations

This dissertation proposes several improvements to existing adversarial attacks against MalConv, a raw-byte malware classifier for Windows PE files. The included contributions greatly improve the success rates and performance of gradient-based file overlay attacks. All improvements are included in a new open-source attack utility called BitCamo.

Several new payload initialization strategies for use with gradient-based attacks are proposed and evaluated as potential replacements for the randomized initialization method used by current attacks. An algorithm for determining the optimal payload size is also proposed. The resulting improvements achieve a 100% evasion rate against eligible target executables using an average payload size …

An Entity-Component System Based, Ieee Dis Interoperability Interface, Noah W. Scott

Theses and Dissertations

In practice, there are several different methods of organizing data within a given software to fulfil its function. The method known as the Entity-Component System (ECS) is a software architecture where data components define entities. These components are stored as organized lists which are operated upon by systems to inject the system's desired behavior. Data is sent across the networks to communicate between simulation nodes as Protocol Data Units (PDUs). When sending PDUs across a network protocol, each simulation represents a common understanding of the world at the desired level of detail. DIS-compliant simulations are commonly written using an Object-Oriented …

Mrim: Enabling Mixed-Resolution Imaging For Low-Power Pervasive Vision Tasks, Jiyan Wu, Vithurson Subasharan, Tuan Tran, Archan Misra

Research Collection School Of Computing and Information Systems

While many pervasive computing applications increasingly utilize real-time context extracted from a vision sensing infrastructure, the high energy overhead of DNN-based vision sensing pipelines remains a challenge for sustainable in-the-wild deployment. One common approach to reducing such energy overheads is the capture and transmission of lower-resolution images to an edge node (where the DNN inferencing task is executed), but this results in an accuracy-vs-energy tradeoff, as the DNN inference accuracy typically degrades with a drop in resolution. In this work, we introduce MRIM, a simple but effective framework to tackle this tradeoff. Under MRIM, the vision sensor platform first executes …

Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry

Theses and Dissertations

The software verification in this thesis concentrates on verifying a particle filter for use in tracking and estimation, a key application area for the Air Force. The development and verification process described in this thesis is a demonstration of the power, limitation, and compromises involved in applying automated software verification tools to critical embedded software applications.

Classifying Dead Code In Software Development, Arman Alavizadeh

University Honors Theses

Dead code pervades as an issue in the world of software development as a source of many famous software disasters such as the ARIANE 5 rocket failure and chemical bank withdrawal error. Defining dead code on narrow levels of granularity has not been fully explored, yet is crucial to better our understanding of dead code. Here we will be starting a discussion on how to approach classifying dead code via comparing dead code research specific to an industry segment. Research will be compared primarily by methodology and limitations. Dead code subtype classifications are gleaned from research comparisons and can serve …

An Investigation Of Data Storage In Entity-Component Systems, Bailey V. Compton

Theses and Dissertations

Entity-Component Systems (ECS) have grown vastly in application since their introduction more than 20 years ago. Providing the ability to efficiently manage data and optimize program execution, ECSs, as well as the wider field of data-oriented design, have attained popularity in the realms of modeling, simulation, and gaming. This manuscript aims to elucidate and document the storage frameworks commonly found in ECSs, as well as suggesting conceptual connections between ECSs and relational databases. This formal documentation of the in-memory storage formats of entity-component systems affords the United States Air Force, the Department of Defense, and the software engineering community a …

Bug Triage Automation Approaches: A Comparative Study, Dr Khaled Nagaty, Madonna Mayez, Khaled Ahmed Nagay Dr.

Computer Science

Bug triage is an essential task in the software maintenance phase. It is the process of assigning a developer (fixer) to bug report. Triaging process is performed by the triager, who has to analyze developers’ profiles and bug reports for the purpose of making a suitable assignment. Manual assignment consumes time, financial resources and human resources; to get a high-quality software with minimum cost, automating this process is necessary. Previous researchers tackled this problem as a classification problem from different perspectives, either information retrieval approach or machine learning algorithms, some researchers handled it as an optimization problem using optimization and …

Revisiting Neuron Coverage Metrics And Quality Of Deep Neural Networks, Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi, David Lo

Research Collection School Of Computing and Information Systems

Deep neural networks (DNN) have been widely applied in modern life, including critical domains like autonomous driving, making it essential to ensure the reliability and robustness of DNN-powered systems. As an analogy to code coverage metrics for testing conventional software, researchers have proposed neuron coverage metrics and coverage-driven methods to generate DNN test cases. However, Yan et al. doubt the usefulness of existing coverage criteria in DNN testing. They show that a coverage-driven method is less effective than a gradient-based method in terms of both uncovering defects and improving model robustness. In this paper, we conduct a replication study of …

Hermes: Using Commit-Issue Linking To Detect Vulnerability-Fixing Commits, Truong Giang Nguyen, Hong Jin Kang, David Lo, Abhishek Sharma, Andrew E. Santosa, Asankhaya Sharma, Ming Yi Ang

Research Collection School Of Computing and Information Systems

Software projects today rely on many third-party libraries, and therefore, are exposed to vulnerabilities in these libraries. When a library vulnerability is fixed, users are notified and advised to upgrade to a new version of the library. However, not all vulnerabilities are publicly disclosed, and users may not be aware of vulnerabilities that may affect their applications. Due to the above challenges, there is a need for techniques which can identify and alert users to silent fixes in libraries; commits that fix bugs with security implications that are not officially disclosed. We propose a machine learning approach to automatically identify …

Gender Influence On Communication Initiated Within Student Teams, Rita Garcia, Chieh-Ju Trinity Liao, Ariane Pearce, Christoph Treude

Research Collection School Of Computing and Information Systems

Collaboration is important during software development, but related work has found gender differences can influence the collaboration process, creating inequality in the team’s dynamics. In this paper, we present a gender analysis study that involved 39 students, examining their teams’ online collaborations while contributing to a large open-source software project. Eight teams of 4-6 Software Engineering (SE) students communicated over an online messaging platform, Slack, to complete an eight-week project. The goal of this study is to identify gender differences emerging from team collaboration. A mixed-methods approach was used to collect students’ teamwork experiences and analyse their collaboration. Our research …

Investigating Collaboration In Software Reverse Engineering, Allison M. Wong

Theses and Dissertations

Reverse engineering (RE) is a rigorous process of exploration and analysis to support software design recovery and exploit development. The process is often conducted in teams to divide the workload and take full advantage of engineers' individual expertise and strengths. Collaboration in RE requires versatile and reliable tools that can match the environment's unpredictable and fluid nature. While studies on collaborative software development have indicated common best practices and implementations, similar standards have not been explored in reverse engineering. This research conducts semi-structured interviews with reverse engineering experts to understand their needs and solutions while working in a team. The …

Patterns Of Academic Help-Seeking In Undergraduate Computing Students, Augie Doebling

Master's Theses

Knowing when and how to seek academic help is crucial to the success of undergraduate computing students. While individual help-seeking resources have been studied, little is understood about the factors influencing students to use or avoid certain re- sources. Understanding students’ patterns of help-seeking can help identify factors contributing to utilization or avoidance of help resources by different groups, an important step toward improving the quality and accessibility of resources. We present a mixed-methods study investigating the help-seeking behavior of undergraduate computing students. We collected survey data (n = 138) about students’ frequency of using several resources followed by one-on-one …

Strangan: Adversarially-Learnt Spatial Transformer For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Archan Misra, Nirmalya Roy

Research Collection School Of Computing and Information Systems

We tackle the problem of domain adaptation for inertial sensing-based human activity recognition (HAR) applications -i.e., in developing mechanisms that allow a classifier trained on sensor samples collected under a certain narrow context to continue to achieve high activity recognition accuracy even when applied to other contexts. This is a problem of high practical importance as the current requirement of labeled training data for adapting such classifiers to every new individual, device, or on-body location is a major roadblock to community-scale adoption of HAR-based applications. We particularly investigate the possibility of ensuring robust classifier operation, without requiring any new labeled …

Jscsp: A Novel Policy-Based Xss Defense Mechanism For Browsers, Guangquan Xu, Xiaofei Xie, Shuhan Huang, Jun Zhang, Lei Pan, Wei Lou, Kaitai Liang

Research Collection School Of Computing and Information Systems

To mitigate cross-site scripting attacks (XSS), the W3C group recommends web service providers to employ a computer security standard called Content Security Policy (CSP). However, less than 3.7 percent of real-world websites are equipped with CSP according to Google’s survey. The low scalability of CSP is incurred by the difficulty of deployment and non-compatibility for state-of-art browsers. To explore the scalability of CSP, in this article, we propose JavaScript based CSP (JSCSP), which is able to support most of real-world browsers but also to generate security policies automatically. Specifically, JSCSP offers a novel self-defined security policy which enforces essential confinements …

Coders Assembly: Peer Assisted Learning Model For Freshman Programming Courses, Kyong Jin Shim, Gottipati Swapna, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

Today, computing graduates see a bright outlook thanks to the high demand for skills driven by the increasing importance of technology as the main driving force behind business transformation. As technology continues to grow exponentially over recent years, computing graduates have some of the highest starting salaries in the market. Even though universities have increased production of computing degree graduates in recent years, it is insufficient to fill the jobs available in the market. Therefore, going forward, the demand is likely to further increase. The continued demand for computing programs in universities has led to an increased intake size, thus …

Analyzing The Impact Of Digital Payment On Efficiency And Productivity Of Commercial Banks: A Case Study In China, Haopeng Wang, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Digital payment has become one of the most popular payment methods all around the world, especially in countries that witnessed the rapid development of internet. As a traditional financial institution, commercial banks have been impacted by newly developed payment technology since third payment platforms have attracted customers to use the digital payment for daily consumption, transferring, and even investment. This paper focuses on analyzing whether and how the commercial banks in China have been affected by digital payment by using empirical methods. Systematic Generalized Method of Moments (SYS-GMM) is used to test the relationship between the productivity of commercial banks …