Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (598)
- Engineering (554)
- Artificial Intelligence and Robotics (453)
- Programming Languages and Compilers (435)
- Computer Engineering (369)
-
- Graphics and Human Computer Interfaces (308)
- Other Computer Sciences (238)
- Information Security (227)
- Theory and Algorithms (204)
- Systems Architecture (197)
- Social and Behavioral Sciences (194)
- OS and Networks (174)
- Business (157)
- Numerical Analysis and Scientific Computing (146)
- Education (140)
- Electrical and Computer Engineering (104)
- Medicine and Health Sciences (97)
- Computer and Systems Architecture (94)
- Data Science (86)
- Digital Communications and Networking (71)
- Operations Research, Systems Engineering and Industrial Engineering (69)
- Communication (54)
- Life Sciences (54)
- Environmental Sciences (53)
- Arts and Humanities (48)
- Technology and Innovation (42)
- Systems Engineering (41)
- Institution
-
- Singapore Management University (2211)
- California Polytechnic State University, San Luis Obispo (206)
- Western University (130)
- Air Force Institute of Technology (124)
- University of Malaya (114)
-
- City University of New York (CUNY) (100)
- California State University, San Bernardino (88)
- MMU Press (74)
- Old Dominion University (72)
- Portland State University (50)
- Edith Cowan University (48)
- United Arab Emirates University (48)
- University of Nevada, Las Vegas (48)
- University of Arkansas, Fayetteville (42)
- Loyola University Chicago (40)
- Chapman University (36)
- San Jose State University (36)
- University of Nebraska - Lincoln (35)
- Kennesaw State University (34)
- Embry-Riddle Aeronautical University (32)
- St. Mary's University (31)
- Rochester Institute of Technology (29)
- The University of Akron (23)
- Purdue University (22)
- University of Dayton (22)
- Technological University Dublin (21)
- Dakota State University (18)
- Universitas Negeri Yogyakarta (17)
- University of Nebraska at Omaha (17)
- Institute of Business Administration (16)
- Keyword
-
- Software engineering (152)
- Software (83)
- Deep learning (80)
- Machine learning (77)
- Software Engineering (62)
-
- Android (60)
- Machine Learning (59)
- Computer Science (52)
- Deep Learning (49)
- Empirical study (47)
- Software development (44)
- Refactoring (42)
- Computer science (38)
- Security (37)
- Programming (36)
- Java (35)
- Software maintenance (34)
- Software testing (34)
- Collaboration (32)
- Model Check (29)
- Testing (29)
- GitHub (27)
- Python (26)
- Stack Overflow (25)
- Data mining (24)
- Visualization (24)
- Artificial Intelligence (23)
- Computer software -- Development (23)
- Large language models (23)
- Empirical software engineering (22)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (2149)
- Theses and Dissertations (144)
- Electrical and Computer Engineering Publications (130)
- Collaborative Agent Design (CAD) Research Center (103)
- Student Works (2000-2009) (103)
-
- Journal of Informatics and Web Engineering (74)
- Theses Digitization Project (73)
- Publications and Research (67)
- Master's Theses (47)
- Dissertations and Theses Collection (Open Access) (40)
- Computer Science: Faculty Publications and Other Works (39)
- Theses (35)
- Computer Science Faculty Publications (31)
- Theses : Honours (28)
- Articles (27)
- Computer Science and Software Engineering (27)
- Computer Engineering (24)
- Open Educational Resources (24)
- Separations Campaign (TRP) (24)
- Williams Honors College, Honors Research Projects (23)
- Computer Science Faculty Publications and Presentations (21)
- Electronic Theses and Dissertations (21)
- Honors Theses (21)
- Computer Science and Computer Engineering Undergraduate Honors Theses (20)
- Faculty Publications (19)
- Dissertations (18)
- Master's Projects (18)
- University Honors Theses (18)
- Elinvo (Electronics, Informatics, and Vocational Education) (17)
- School of Computing: Dissertations, Theses, and Student Research (17)
- Publication Type
- File Type
Articles 751 - 780 of 4404
Full-Text Articles in Software Engineering
Exgen: Ready-To-Use Exercise Generation In Introductory Programming Courses, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna
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 …
Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei
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, Moomal Farhad Farhad
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, Souheil Abdel-Latif Akacha
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, Chong Cher Chia
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, Urvashi Kishnani
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, Matthew Jensen
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, Huned Yusufbhai Materwala
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, Martin Feick, Andre Zenner, Oscar Ariza, Anthony Tang, Cihan Biyikli, Antonio Kruger
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, Duy Tai Nguyen, Hong Long Pham, Jun Sun, Quang Loc Le
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 …
Towards Llm-Based Fact Verification On News Claims With A Hierarchical Step-By-Step Prompting Method, Xuan Zhang, Wei Gao
Towards Llm-Based Fact Verification On News Claims With A Hierarchical Step-By-Step Prompting Method, Xuan Zhang, Wei Gao
Research Collection School Of Computing and Information Systems
While large pre-trained language models (LLMs) have shown their impressive capabilities in various NLP tasks, they are still underexplored in the misinformation domain. In this paper, we examine LLMs with in-context learning (ICL) for news claim verification, and find that only with 4-shot demonstration examples, the performance of several prompting methods can be comparable with previous supervised models. To further boost performance, we introduce a Hierarchical Step-by-Step (HiSS) prompting method which directs LLMs to separate a claim into several subclaims and then verify each of them via multiple questionsanswering steps progressively. Experiment results on two public misinformation datasets show that …
Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei
Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei
Theses
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 Novel Multi-Model Patient Similarity Network Driven By Federated Data Quality And Resource Profiling, Alramzana Nujum Navaz
A Novel Multi-Model Patient Similarity Network Driven By Federated Data Quality And Resource Profiling, Alramzana Nujum Navaz
Dissertations
Smart and Connected Health (SCH) is revolutionizing healthcare by leveraging extensive healthcare data for precise, personalized medicine. At its core, SCH relies on the concept of patient similarity, which involves the comparative analysis of newly encountered patients with those who exhibit comparable similarities from the existing patient cohort. Yet, this approach faces significant challenges, including data heterogeneity and dimensionality. Our research introduces a multi-dimensional Patient Similarity Network (PSN) Fusion model tailored to handle both static and dynamic features. The static data analysis focuses on extracting contextual information using Bidirectional Encoder Representations from Transformers (BERT), while dynamic features are captured through …
Github Actions: The Impact On The Pull Request Process, Mairieli Wessel, Joseph Vargovich, Marco Gerosa, Christoph Treude
Github Actions: The Impact On The Pull Request Process, Mairieli Wessel, Joseph Vargovich, Marco Gerosa, Christoph Treude
Research Collection School Of Computing and Information Systems
Software projects frequently use automation tools to perform repetitive activities in the distributed software development process. Recently, GitHub introduced GitHub Actions, a feature providing automated workflows for software projects. Understanding and anticipating the effects of adopting such technology is important for planning and management. Our research investigates how projects use GitHub Actions, what the developers discuss about them, and how project activity indicators change after their adoption. Our results indicate that 1,489 out of 5,000 most popular repositories (almost 30% of our sample) adopt GitHub Actions and that developers frequently ask for help implementing them. Our findings also suggest that …
Autolog: A Log Sequence Synthesis Framework For Anomaly Detection, Yintong Huo, Yichen Li, Yuxin Su, Pinjia He, Zifan Xie, R. Michael Lyu
Autolog: A Log Sequence Synthesis Framework For Anomaly Detection, Yintong Huo, Yichen Li, Yuxin Su, Pinjia He, Zifan Xie, R. Michael Lyu
Research Collection School Of Computing and Information Systems
The rapid progress of modern computing systems has led to a growing interest in informative run-time logs. Various log-based anomaly detection techniques have been proposed to ensure software reliability. However, their implementation in the industry has been limited due to the lack of high-quality public log resources as training datasets.While some log datasets are available for anomaly detection, they suffer from limitations in (1) comprehensiveness of log events; (2) scalability over diverse systems; and (3) flexibility of log utility. To address these limitations, we propose AutoLog, the first automated log generation methodology for anomaly detection. AutoLog uses program analysis to …
Quantumeyes: Towards Better Interpretability Of Quantum Circuits, Shaolun Ruan, Qiang Guan, Paul Griffin, Ying Mao, Yong Wang
Quantumeyes: Towards Better Interpretability Of Quantum Circuits, Shaolun Ruan, Qiang Guan, Paul Griffin, Ying Mao, Yong Wang
Research Collection School Of Computing and Information Systems
Quantum computing offers significant speedup compared to classical computing, which has led to a growing interest among users in learning and applying quantum computing across various applications. However, quantum circuits, which are fundamental for implementing quantum algorithms, can be challenging for users to understand due to their underlying logic, such as the temporal evolution of quantum states and the effect of quantum amplitudes on the probability of basis quantum states. To fill this research gap, we propose QuantumEyes, an interactive visual analytics system to enhance the interpretability of quantum circuits through both global and local levels. For the global-level analysis, …
Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement, Souheil Abdel-Latif Akacha
Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement, Souheil Abdel-Latif Akacha
Theses
The rapid adoption of Learning Management Systems (LMSs) like Moodle, Chamilo, and Ilias became essential for online education due to the Coronavirus Disease 2019 (COVID-19) pandemic, revolutionizing online learning while exposing security vulnerabilities. This thesis explores security concerns within these LMSs across different pandemic periods. By analyzing existing patches, security measures, and emerging cybersecurity technologies, recommendations are formulated to enhance LMS security against evolving cyber threats, providing actionable insights for educational institutions to ensure secure online education continuity. The numerical findings highlight the increasing need for proactive security measures in Moodle, the fluctuating nature of vulnerabilities in Chamilo, and the …
A Novel Multidimensional Reference Model For Heterogeneous Textual Datasets Using Context, Semantic And Syntactic Clues, Ganesh Kumar, Shuib Basri, Abdullahi Abubakar Imam, Abdullateef Abdullateef Oluwagbemiga Balogun, Hussaini Mamman, Luiz Fernando Capretz
A Novel Multidimensional Reference Model For Heterogeneous Textual Datasets Using Context, Semantic And Syntactic Clues, Ganesh Kumar, Shuib Basri, Abdullahi Abubakar Imam, Abdullateef Abdullateef Oluwagbemiga Balogun, Hussaini Mamman, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
With the advent of technology and use of latest devices, they produces voluminous data. Out of it, 80% of the data are unstructured and remaining 20% are structured and semi-structured. The produced data are in heterogeneous format and without following any standards. Among heterogeneous (structured, semi-structured and unstructured) data, textual data are nowadays used by industries for prediction and visualization of future challenges. Extracting useful information from it is really challenging for stakeholders due to lexical and semantic matching. Few studies have been solving this issue by using ontologies and semantic tools, but the main limitations of proposed work were …
Habit-Tracking Application For Individuals With Attention Deficit Hyperactivity Disorder (Adhd), Hannah Wishon
Habit-Tracking Application For Individuals With Attention Deficit Hyperactivity Disorder (Adhd), Hannah Wishon
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
This project aims to create a habit-tracking app that would cater to the needs of those with ADHD while being accessible enough to be used by the general, neurotypical public.
Teacher Candidates’ Conceptions And Practices Of Computational Thinking For Equity, Heather F. Clark, Symone A. Gyles, Imelda Nava-Landeros
Teacher Candidates’ Conceptions And Practices Of Computational Thinking For Equity, Heather F. Clark, Symone A. Gyles, Imelda Nava-Landeros
Journal of Computer Science Integration
This study documents novice science and math teachers’ developing pedagogical approaches to integrating computational thinking (CT) and data into their courses to support educational equity and social justice. The 10 novice teacher candidates (TCs) studied were part of an urban teacher residency program that empowered them with an asset-based pedagogy we describe as “CT for Equity.” Drawing on coursework and interviews as data, we asked three questions: What are teachers’ conceptions of CT? What are their CT instructional practices? And how did their students respond to those practices? To explore conceptions of CT, we used Kafai et al.’s (2020) articulation …
Service-Oriented Framework For Developing Interoperable E-Health Systems In A Low-Income Country, Bonface Abima, Agnes Nakakawa, Geoffrey Mayoka Kituyi
Service-Oriented Framework For Developing Interoperable E-Health Systems In A Low-Income Country, Bonface Abima, Agnes Nakakawa, Geoffrey Mayoka Kituyi
The African Journal of Information Systems
e-Health solutions in low-income countries are fragmented, address institution-specific needs, and do little to address the strategic need for inter-institutional exchange of health data. Although various e-health interoperability frameworks exist, contextual factors often hinder their effective adoption in low-income countries. This underlines the need to investigate such factors and to use findings to adapt existing e-health interoperability models. Following a design science approach, this research involved conducting an exploratory survey among 90 medical and Information Technology personnel from 67 health facilities in Uganda. Findings were used to derive requirements for e-health interoperability, and to orchestrate elements of a service oriented …
Peatmoss: Mining Pre-Trained Models In Open-Source Software, Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajiv Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis
Peatmoss: Mining Pre-Trained Models In Open-Source Software, Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajiv Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis
Computer Science: Faculty Publications and Other Works
Developing and training deep learning models is expensive, so software engineers have begun to reuse pre-trained deep learning models (PTMs) and fine-tune them for downstream tasks. Despite the widespread use of PTMs, we know little about the corresponding software engineering behaviors and challenges. To enable the study of software engineering with PTMs, we present the PeaTMOSS dataset: Pre-Trained Models in Open-Source Software. PeaTMOSS has three parts: a snapshot of (1) 281,638 PTMs, (2) 27,270 open-source software repositories that use PTMs, and (3) a mapping between PTMs and the projects that use them. We challenge PeaTMOSS miners to discover software engineering …
Enhancing Autism Education: Exploring Interactive Videos And Ai Integration For Effective Teaching, Fatima Ahmed Alraeesi
Enhancing Autism Education: Exploring Interactive Videos And Ai Integration For Effective Teaching, Fatima Ahmed Alraeesi
Thesis/ Dissertation Defenses
Teachers should be aware of how to develop effective teaching methods for students with autism. To achieve the best results, teachers need to thoroughly understand autism and the teaching methods and modifications that work best for these students. Adapting classwork & homework and helping students with language difficulties are effective teaching methods. Teachers can use books to get the necessary information and guidance or take training courses. Keeping students organized and focused is one of the needs of children with autism, as well as the use of visual strategies. Some teachers rely on fixed routines in teaching autistic children. Therefore, …
Software Testing And Code Refactoring: A Survey With Practitioners, Danilo Leandro Lima, Ronnie Souza Santos, Guilherme Pires Garcia, Sildemir S. Silva, Cesar Franca, Luiz Fernando Capretz
Software Testing And Code Refactoring: A Survey With Practitioners, Danilo Leandro Lima, Ronnie Souza Santos, Guilherme Pires Garcia, Sildemir S. Silva, Cesar Franca, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
Nowadays, software testing professionals are commonly required to develop coding skills to work on test automation. One essential skill required from those who code is the ability to implement code refactoring, a valued quality aspect of software development; however, software developers usually encounter obstacles in successfully applying this practice. In this scenario, the present study aims to explore how software testing professionals (e.g., software testers, test engineers, test analysts, and software QAs) deal with code refactoring to understand the benefits and limitations of this practice in the context of software testing. We followed the guidelines to conduct surveys in software …
The Role Of Feedback Within Scrum For Engineering Department Operations, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu
The Role Of Feedback Within Scrum For Engineering Department Operations, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu
Posters
The Scrum framework is built on the principles of inspection and adaptation. Feedback drives the inspection process, and the team adapts based on that feedback to optimize its performance and outcomes. Within engineering departments, Scrum requires departments to examine how and when feedback is obtained to ensure that the department is remaining agile. This poster illustrates the role of feedback within two Scrum teams, one focused on student success and the other focused on faculty rewards and incentives. The two cases emphasize the need for continuous introspection at team and department levels.
Constructing Cyber-Physical System Testing Suites Using Active Sensor Fuzzing, Fan. Zhang, Qianmei. Wu, Bohan. Xuan, Yuqi. Chen, Wei. Lin, Christopher M. Poskitt, Jun Sun, Binbin. Chen
Constructing Cyber-Physical System Testing Suites Using Active Sensor Fuzzing, Fan. Zhang, Qianmei. Wu, Bohan. Xuan, Yuqi. Chen, Wei. Lin, Christopher M. Poskitt, Jun Sun, Binbin. Chen
Research Collection School Of Computing and Information Systems
Cyber-physical systems (CPSs) automating critical public infrastructure face a pervasive threat of attack, motivating research into different types of countermeasures. Assessing the effectiveness of these countermeasures is challenging, however, as benchmarks are difficult to construct manually, existing automated testing solutions often make unrealistic assumptions, and blindly fuzzing is ineffective at finding attacks due to the enormous search spaces and resource requirements. In this work, we propose active sensor fuzzing , a fully automated approach for building test suites without requiring any a prior knowledge about a CPS. Our approach employs active learning techniques. Applied to a real-world water treatment system, …
Exploring Approaches To Engage K-12 Students In Learning Computational Thinking Using Collaborative Robots, Zoila Anuri Kanu
Exploring Approaches To Engage K-12 Students In Learning Computational Thinking Using Collaborative Robots, Zoila Anuri Kanu
College of Engineering Summer Undergraduate Research Program
Minority students are largely underrepresented in the STEM field. The goal for this project was to develop a program which promotes the inclusion of computation skills among students and help them work collaboratively with the use of human – robot interaction. Robots are such a strong tool that can be used to enhance computational thinking and engage students towards a technical field. Through workshops and readings about computational thinking we worked on building a block-based program that introduces the uses of robots as teaching tool for computational thinking.
Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini
Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini
College of Engineering Summer Undergraduate Research Program
No abstract provided.
Using The Typescript Compiler To Fix Erroneous Node.Js Snippets, Brittany Reid, Christoph Treude, Markus Wagner
Using The Typescript Compiler To Fix Erroneous Node.Js Snippets, Brittany Reid, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
Most online code snippets do not run. This means that developers looking to reuse code from online sources must manually find and fix errors. We present an approach for automatically evaluating and correcting errors in Node.js code snippets: Node Code Correction (NCC). NCC leverages the ability of the TypeScript compiler to generate errors and inform code corrections through the combination of TypeScript’s builtin codefixes, our own targeted fixes, and deletion of erroneous lines. Compared to existing approaches using linters, our findings suggest that NCC is capable of detecting a larger number of errors per snippet and more error types, and …
Problems In Microservice Development: Supporting Visualisation, Oscar Manglaras, Alex Farkas, Peter Fule, Christoph Treude, Markus Wagner
Problems In Microservice Development: Supporting Visualisation, Oscar Manglaras, Alex Farkas, Peter Fule, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
In microservice architectures, developers can face significant problems understanding the structure of the system and how the different microservices interact. This difficulty results from the distributed nature of the system, and the abundance of inter-service communication within the architecture. We want to determine if network visualisations can address these problems given their ability to convey complex topologies. However, to identify what architectural characteristics should be visualised, and how this should be done, we must first determine the needs of microservice developers. This paper identifies and presents the impact and frequency of problems faced by a cohort of microservice developers using …