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Articles 961 - 990 of 6720

Full-Text Articles in Physical Sciences and Mathematics

On Analysing Student Resilience In Higher Education Programs Using A Data-Driven Approach, Audrey Tedja Widjaja, Ee Peng Lim, Aldy Gunawan Dec 2021

On Analysing Student Resilience In Higher Education Programs Using A Data-Driven Approach, Audrey Tedja Widjaja, Ee Peng Lim, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Analysing student resilience is important as research has shown that resilience is related to students’ academic performance and their persistence through academic setbacks. While questionnaires can be conducted to assess student resilience directly, they suffer from human recall errors and deliberate suppression of true responses. In this paper, we propose ACREA, ACademic REsilience Analytics framework which adopts a datadriven approach to analyse student resilient behavior with the use of student-course data. ACREA defines academic setbacks experienced by students and measures how well students overcome such setbacks using a quasi-experimental design. By applying ACREA on a real world student-course dataset, we …

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Microservices Orchestration Vs. Choreography: A Decision Framework, Alan @ Ali Madjelisi Megargel, Christopher M. Poskitt, Shankararaman, Venky Dec 2021

Microservices Orchestration Vs. Choreography: A Decision Framework, Alan @ Ali Madjelisi Megargel, Christopher M. Poskitt, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

Microservices-based applications consist of loosely coupled, independently deployable services that encapsulate units of functionality. To implement larger application processes, these microservices must communicate and collaborate. Typically, this follows one of two patterns: (1) choreography, in which communication is done via asynchronous message-passing; or (2) orchestration, in which a controller is used to synchronously manage the process flow. Choosing the right pattern requires the resolution of some trade-offs concerning coupling, chattiness, visibility, and design. To address this problem, we propose a decision framework for microservices collaboration patterns that helps solution architects to crystallize their goals, compare the key factors, and then …

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Efficient Data Structures For Text Processing Applications, Paniz Abedin Dec 2021

Efficient Data Structures For Text Processing Applications, Paniz Abedin

Electronic Theses and Dissertations, 2020-2023

This thesis is devoted to designing and analyzing efficient text indexing data structures and associated algorithms for processing text data. The general problem is to preprocess a given text or a collection of texts into a space-efficient index to quickly answer various queries on this data. Basic queries such as counting/reporting a given pattern's occurrences as substrings of the original text are useful in modeling critical bioinformatics applications. This line of research has witnessed many breakthroughs, such as the suffix trees, suffix arrays, FM-index, etc. In this work, we revisit the following problems: 1. The Heaviest Induced Ancestors problem 2. …

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Fair And Diverse Group Formation Based On Multidimensional Features, Mohammed Saad A Alqahtani Dec 2021

Fair And Diverse Group Formation Based On Multidimensional Features, Mohammed Saad A Alqahtani

Graduate Theses and Dissertations

The goal of group formation is to build a team to accomplish a specific task. Algorithms are being developed to improve the team's effectiveness so formed and the efficiency of the group selection process. However, there is concern that team formation algorithms could be biased against minorities due to the algorithms themselves or the data on which they are trained. Hence, it is essential to build fair team formation systems that incorporate demographic information into the process of building the group. Although there has been extensive work on modeling individuals’ expertise for expert recommendation and/or team formation, there has been …

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A Fine-Grained Attribute Based Data Retrieval With Proxy Re-Encryption Scheme For Data Outsourcing Systems, Hanshu Hong, Ximeng Liu, Zhixin Sun Dec 2021

A Fine-Grained Attribute Based Data Retrieval With Proxy Re-Encryption Scheme For Data Outsourcing Systems, Hanshu Hong, Ximeng Liu, Zhixin Sun

Research Collection School Of Computing and Information Systems

Attribute based encryption is suitable for data protection in data outsourcing systems such as cloud computing. However, the leveraging of encryption technique may retrain some routine operations over the encrypted data, particularly in the field of data retrieval. This paper presents an attribute based date retrieval with proxy re-encryption (ABDR-PRE) to provide both fine-grained access control and retrieval over the ciphertexts. The proposed scheme achieves fine-grained data access management by adopting KP-ABE mechanism, a delegator can generate the re-encryption key and search indexes for the ciphertexts to be shared over the target delegatee’s attributes. Throughout the process of data sharing, …

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Vireo @ Trecvid 2021 Ad-Hoc Video Search, Jiaxin Wu, Phuong Anh Nguyen, Chong-Wah Ngo Dec 2021

Vireo @ Trecvid 2021 Ad-Hoc Video Search, Jiaxin Wu, Phuong Anh Nguyen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In this paper, we summarize our submitted runs and results for Ad-hoc Video Search (AVS) task at TRECVid 2020

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Imon: Appearance-Based Gaze Tracking System On Mobile Devices, Sinh Huynh, Rajesh Krishna Balan, Jeonggil Ko Dec 2021

Imon: Appearance-Based Gaze Tracking System On Mobile Devices, Sinh Huynh, Rajesh Krishna Balan, Jeonggil Ko

Research Collection School Of Computing and Information Systems

Gaze tracking is a key building block used in many mobile applications including entertainment, personal productivity, accessibility, medical diagnosis, and visual attention monitoring. In this paper, we present iMon, an appearance-based gaze tracking system that is both designed for use on mobile phones and has significantly greater accuracy compared to prior state-of-the-art solutions. iMon achieves this by comprehensively considering the gaze estimation pipeline and then overcoming three different sources of errors. First, instead of assuming that the user's gaze is fixed to a single 2D coordinate, we construct each gaze label using a probabilistic 2D heatmap gaze representation input to …

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Spurring Digital Transformation In Singapore's Legal Industry, Xin Juan Chua, Steven M. Miller Dec 2021

Spurring Digital Transformation In Singapore's Legal Industry, Xin Juan Chua, Steven M. Miller

Research Collection School Of Computing and Information Systems

COVID-19 has transformed the way we live and work. It has caused the processes and operations of businesses and organisations to be restructured, as well as transformed business models. A 2020 McKinsey Global survey reported that companies all over the world claim they have accelerated the digitalisation of their customer and supply-chain interactions, as well as their internal operations, by three to four years. They also said they thought the share of digital or digitally enabled products in their portfolios has advanced by seven years. While technology transformation is not new to the legal profession, COVID-19 has cemented the importance …

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Neurolkh: Combining Deep Learning Model With Lin-Kernighan-Helsgaun Heuristic For Solving The Traveling Salesman Problem, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang Dec 2021

Neurolkh: Combining Deep Learning Model With Lin-Kernighan-Helsgaun Heuristic For Solving The Traveling Salesman Problem, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

We present NeuroLKH, a novel algorithm that combines deep learning with the strong traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem. Specifically, we train a Sparse Graph Network (SGN) with supervised learning for edge scores and unsupervised learning for node penalties, both of which are critical for improving the performance of LKH. Based on the output of SGN, NeuroLKH creates the edge candidate set and transforms edge distances to guide the searching process of LKH. Extensive experiments firmly demonstrate that, by training one model on a wide range of problem sizes, NeuroLKH significantly outperforms LKH and generalizes well to …

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Learning To Iteratively Solve Routing Problems With Dual-Aspect Collaborative Transformer, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang Dec 2021

Learning To Iteratively Solve Routing Problems With Dual-Aspect Collaborative Transformer, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang

Research Collection School Of Computing and Information Systems

Recently, Transformer has become a prevailing deep architecture for solving vehicle routing problems (VRPs). However, it is less effective in learning improvement models for VRP because its positional encoding (PE) method is not suitable in representing VRP solutions. This paper presents a novel Dual-Aspect Collaborative Transformer (DACT) to learn embeddings for the node and positional features separately, instead of fusing them together as done in existing ones, so as to avoid potential noises and incompatible correlations. Moreover, the positional features are embedded through a novel cyclic positional encoding (CPE) method to allow Transformer to effectively capture the circularity and symmetry …

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Towards Non-Intrusive Camera-Based Heart Rate Variability Estimation In The Car Under Naturalistic Condition, Shu Liu, Kevin Koch, Zimu Zhou, Martin Maritsch, Xiaoxi He, Elgar Fleisch, Felix Wortmann Dec 2021

Towards Non-Intrusive Camera-Based Heart Rate Variability Estimation In The Car Under Naturalistic Condition, Shu Liu, Kevin Koch, Zimu Zhou, Martin Maritsch, Xiaoxi He, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

Driver status monitoring systems are a vital component of smart cars in the future, especially in the era when an increasing amount of time is spent in the vehicle. The heart rate (HR) is one of the most important physiological signals of driver status. To infer HR of drivers, the mainstream of existing research focused on capturing subtle heartbeat-induced vibration of the torso or leveraged photoplethysmography (PPG) that detects cardiac cycle-related blood volume changes in the microvascular. However, existing approaches rely on dedicated sensors that are expensive and cumbersome to be integrated or are vulnerable to ambient noise. Moreover, their …

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On Analysing Student Resilience In Higher Education Programs Using A Data-Driven Approach, Audrey Tedja Widjaja, Ee-Peng Lim, Aldy Gunawan Dec 2021

On Analysing Student Resilience In Higher Education Programs Using A Data-Driven Approach, Audrey Tedja Widjaja, Ee-Peng Lim, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Analysing student resilience is important as research has shown that resilience is related to students’ academic performance and their persistence through academic setbacks. While questionnaires can be conducted to assess student resilience directly, they suffer from human recall errors and deliberate suppression of true responses. In this paper, we propose ACREA, ACademic REsilience Analytics framework which adopts a data-driven approach to analyse student resilient behavior with the use of student-course data. ACREA defines academic setbacks experienced by students and measures how well students overcome such setbacks using a quasi-experimental design. By applying ACREA on a real world student-course dataset, we …

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Empirical Evaluation Of Minority Oversampling Techniques In The Context Of Android Malware Detection, Lwin Khin Shar, Nguyen Binh Duong Ta, David Lo Dec 2021

Empirical Evaluation Of Minority Oversampling Techniques In The Context Of Android Malware Detection, Lwin Khin Shar, Nguyen Binh Duong Ta, David Lo

Research Collection School Of Computing and Information Systems

In Android malware classification, the distribution of training data among classes is often imbalanced. This causes the learning algorithm to bias towards the dominant classes, resulting in mis-classification of minority classes. One effective way to improve the performance of classifiers is the synthetic generation of minority instances. One pioneer technique in this area is Synthetic Minority Oversampling Technique (SMOTE) and since its publication in 2002, several variants of SMOTE have been proposed and evaluated on various imbalanced datasets. However, these techniques have not been evaluated in the context of Android malware detection. Studies have shown that the performance of SMOTE …

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Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng Dec 2021

Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng

Research Collection School Of Computing and Information Systems

A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perform a context-aware OD prediction based on a large-scale public transportation dataset in Singapore. Compared with the baseline Markov-Chain algorithm and GCN, the proposed hybrid GCN-MC model improves the prediction accuracy by 37% and 12% respectively. Lastly, the addition of temporal and historical contextual information further improves the performance of the proposed hybrid model by 4 –12%.

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Robust Bipoly-Matching For Multi-Granular Entities, Ween Jiann Lee, Maksim Tkachenko, Hady W. Lauw Dec 2021

Robust Bipoly-Matching For Multi-Granular Entities, Ween Jiann Lee, Maksim Tkachenko, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Entity matching across two data sources is a prevalent need in many domains, including e-commerce. Of interest is the scenario where entities have varying granularity, e.g., a coarse product category may match multiple finer categories. Previous work in one-to-many matching generally presumes the `one' necessarily comes from a designated source and the `many' from the other source. In contrast, we propose a novel formulation that allows concurrent one-to-many bidirectional matching in any direction. Beyond flexibility, we also seek matching that is more robust to noisy similarity values arising from diverse entity descriptions, by introducing receptivity and reclusivity notions. In addition …

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Channel Integration Services In Online Healthcare Communities, Anqi Zhao, Qian Tang Dec 2021

Channel Integration Services In Online Healthcare Communities, Anqi Zhao, Qian Tang

Research Collection School Of Computing and Information Systems

In online healthcare communities, channel integration services have become the bridge between online and offline channels, enabling patients to easily migrate across channels. Different from pure online services, online-to-offline (On2Off) and offline-to-online (Off2On) channel integration services involve both channels. This study examines the interrelationships between pure online services and channel integration services. Using a panel dataset composed of data from an online healthcare community, we find that pure online services decrease patients’ demand for On2Off integration services but increase their use of Off2On integration services. Our findings suggest that providing healthcare services online can reduce online patients’ needs to visit …

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Canita: Faster Rates For Distributed Convex Optimization With Communication Compression, Zhize Li, Peter Richtarik Dec 2021

Canita: Faster Rates For Distributed Convex Optimization With Communication Compression, Zhize Li, Peter Richtarik

Research Collection School Of Computing and Information Systems

Due to the high communication cost in distributed and federated learning, methods relying on compressed communication are becoming increasingly popular. Besides, the best theoretically and practically performing gradient-type methods invariably rely on some form of acceleration/momentum to reduce the number of communications (faster convergence), e.g., Nesterov's accelerated gradient descent (Nesterov, 1983, 2004) and Adam (Kingma and Ba, 2014). In order to combine the benefits of communication compression and convergence acceleration, we propose a \emph{compressed and accelerated} gradient method based on ANITA (Li, 2021) for distributed optimization, which we call CANITA. Our CANITA achieves the \emph{first accelerated rate} $O\bigg(\sqrt{\Big(1+\sqrt{\frac{\omega^3}{n}}\Big)\frac{L}{\epsilon}} + \omega\big(\frac{1}{\epsilon}\big)^{\frac{1}{3}}\bigg)$, …

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The Development Of Qmms: A Case Study For Reliable Online Quiz Maker And Management System, Mohamed Abdelmoneim Elshafey Dr., Tarek Said Ghoniemy Dr. Nov 2021

The Development Of Qmms: A Case Study For Reliable Online Quiz Maker And Management System, Mohamed Abdelmoneim Elshafey Dr., Tarek Said Ghoniemy Dr.

Future Computing and Informatics Journal

The e-learning and assessment systems became a dominant technology nowadays and distribute across the globe. With severe consequences of COVID19-like crises, the key importance of such technology appeared in which courses, quizzes and questionnaires have to be conducted remotely. Moreover, the use of Learning Management Systems (LMSs), such as blackboard, eCollege, and Moodle, has been sanctioned in all respects of education. This paper presents an open-source interactive Quiz Maker and Management System (QMMS) that suits the research, education (under-grad, grad, or post-grad), and industrial organizations to perform distant quizzes, training and questionnaires with an integration facility with other LMS tools …

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Teaching And Learning Under Covid-19 Public Health Edicts: The Role Of Household Lockdowns And Prior Technology Usage, Neil Guppy, David Boud, Tania Heap, Dominique Verpoorten, Uwe Matzat, Joanna Tai, Louise Lutze-Mann, Mary Roth, Patsie Polly, Jamie-Lee Burgess, Jenilyn L. Agapito, Silvia K. Bartolic Nov 2021

Teaching And Learning Under Covid-19 Public Health Edicts: The Role Of Household Lockdowns And Prior Technology Usage, Neil Guppy, David Boud, Tania Heap, Dominique Verpoorten, Uwe Matzat, Joanna Tai, Louise Lutze-Mann, Mary Roth, Patsie Polly, Jamie-Lee Burgess, Jenilyn L. Agapito, Silvia K. Bartolic

Department of Information Systems & Computer Science Faculty Publications

Public health edicts necessitated by COVID-19 prompted a rapid pivot to remote online teaching and learning. Two major consequences followed: households became students' main learning space, and technology became the sole medium of instructional delivery. We use the ideas of "digital disconnect" and "digital divide" to examine, for students and faculty, their prior experience with, and proficiency in using, learning technology. We also explore, for students, how household lockdowns and digital capacity impacted learning. Our findings are drawn from 3806 students and 283 faculty instructors from nine higher education institutions across Asia, Australia, Europe, and North America. For instructors, we …

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Managing Incomplete Data In The Patient Discharge Summary To Support Correct Hospital Reimbursements, Fadi Naser Eddin Nov 2021

Managing Incomplete Data In The Patient Discharge Summary To Support Correct Hospital Reimbursements, Fadi Naser Eddin

USF Tampa Graduate Theses and Dissertations

The patient discharge summary is a document that conveys the patient's story to other healthcare practitioners, external users, and, most importantly from a financial perspective, health insurers. A defect or incompleteness in the patient's discharge summary will result in delays in the collection process through denial of the entire or partial reimbursement claim or, in the best-case scenario, delay until the discharge summary issue is resolved. The purpose of this project is to address the issue of the incompleteness of discharge summary from the perspective of healthcare providers, with the goal of understanding, diagnosing, and intervening in the research problem. …

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Pre-Earthquake Ionospheric Perturbation Identification Using Cses Data Via Transfer Learning, Pan Xiong, Cheng Long, Huiyu Zhou, Roberto Battiston, Angelo De Santis, Dimitar Ouzounov, Xuemin Zhang, Xuhui Shen Nov 2021

Pre-Earthquake Ionospheric Perturbation Identification Using Cses Data Via Transfer Learning, Pan Xiong, Cheng Long, Huiyu Zhou, Roberto Battiston, Angelo De Santis, Dimitar Ouzounov, Xuemin Zhang, Xuhui Shen

Mathematics, Physics, and Computer Science Faculty Articles and Research

During the lithospheric buildup to an earthquake, complex physical changes occur within the earthquake hypocenter. Data pertaining to the changes in the ionosphere may be obtained by satellites, and the analysis of data anomalies can help identify earthquake precursors. In this paper, we present a deep-learning model, SeqNetQuake, that uses data from the first China Seismo-Electromagnetic Satellite (CSES) to identify ionospheric perturbations prior to earthquakes. SeqNetQuake achieves the best performance [F-measure (F1) = 0.6792 and Matthews correlation coefficient (MCC) = 0.427] when directly trained on the CSES dataset with a spatial window centered on the earthquake epicenter with the Dobrovolsky …

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Mapping E-Commerce Locally And Beyond: Citt K12 Special Investigation Project, Thomas O’Brien, Deanna Matsumoto Nov 2021

Mapping E-Commerce Locally And Beyond: Citt K12 Special Investigation Project, Thomas O’Brien, Deanna Matsumoto

Mineta Transportation Institute

As all aspects of the American workplace become automated or digitally enhanced to some degree, K12 educators have an increasing responsibility to help their students acquire the technical skills necessary to organize and interpret information. Increasingly, this is done through Geographic Information Systems (GIS), especially in careers related to transportation and logistics. The Center for International Trade & Transportation (CITT) at CSU Long Beach has developed this K12 Special Investigation Project to introduce ArcGIS StoryMaps, an engaging, accessible and sophisticated web-based GIS application. The lessons center on e-commerce and its accompanying environmental and economic impact. Still, the activities can be …

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Topic-Aware Heterogeneous Graph Neural Network For Link Prediction, Siyong Xu, Cheng Yang, Yuan Fang, Yuan Fang, Yang Tianchi, Luhao Zhang Nov 2021

Topic-Aware Heterogeneous Graph Neural Network For Link Prediction, Siyong Xu, Cheng Yang, Yuan Fang, Yuan Fang, Yang Tianchi, Luhao Zhang

Research Collection School Of Computing and Information Systems

Heterogeneous graphs (HGs), consisting of multiple types of nodes and links, can characterize a variety of real-world complex systems. Recently, heterogeneous graph neural networks (HGNNs), as a powerful graph embedding method to aggregate heterogeneous structure and attribute information, has earned a lot of attention. Despite the ability of HGNNs in capturing rich semantics which reveal different aspects of nodes, they still stay at a coarse-grained level which simply exploits structural characteristics. In fact, rich unstructured text content of nodes also carries latent but more fine-grained semantics arising from multi-facet topic-aware factors, which fundamentally manifest why nodes of different types would …

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A Bert-Based Two-Stage Model For Chinese Chengyu Recommendation, Minghuan Tan, Jing Jiang, Bingtian Dai Nov 2021

A Bert-Based Two-Stage Model For Chinese Chengyu Recommendation, Minghuan Tan, Jing Jiang, Bingtian Dai

Research Collection School Of Computing and Information Systems

In Chinese, Chengyu are fixed phrases consisting of four characters. As a type of idioms, their meanings usually cannot be derived from their component characters. In this paper, we study the task of recommending a Chengyu given a textual context. Observing some of the limitations with existing work, we propose a two-stage model, where during the first stage we re-train a Chinese BERT model by masking out Chengyu from a large Chinese corpus with a wide coverage of Chengyu. During the second stage, we fine-tune the retrained, Chengyu-oriented BERT on a specific Chengyu recommendation dataset. We evaluate this method on …

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Does Active Service Intervention Drive More Complaints On Social Media? The Roles Of Service Quality And Awareness, Shujing Sun, Yang Gao, Huaxia Rui Nov 2021

Does Active Service Intervention Drive More Complaints On Social Media? The Roles Of Service Quality And Awareness, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

Despite many advantages of social media as a customer service channel, there is a concern that active service intervention encourages excessive service complaints. Our paper casts doubt on this misconception by examining the dynamics between social media customer complaints and brand service interventions. We find service interventions indeed cause more complaints, yet this increase is driven by service awareness rather than chronic complaining. Due to the publicity and connectivity of social media, customers learn about the new service channel by observing customer service delivery to others – a mechanism that is unique to social media customer service and does not …

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Binary Classifiers For Noisy Datasets: A Comparative Study Of Existing Quantum Machine Learning Frameworks And Some New Approaches, Nikolaos Schetakis, Davit Aghamalyan, Paul Robert Griffin, Michael Boguslavsky Nov 2021

Binary Classifiers For Noisy Datasets: A Comparative Study Of Existing Quantum Machine Learning Frameworks And Some New Approaches, Nikolaos Schetakis, Davit Aghamalyan, Paul Robert Griffin, Michael Boguslavsky

Research Collection School Of Computing and Information Systems

This technology offer is a quantum machine learning algorithm applied to binary classification models for noisy datasets which are prevalent in financial and other datasets. By combining hybrid-neural networks, quantum parametric circuits, and data re-uploading we have improved the classification of non-convex 2-dimensional figures by understanding learning stability as noise increases in the dataset. The metric we use for assessing the performance of our quantum classifiers is the area under the receiver operator curve (ROC AUC). We are interested to collaborate with partners with use cases for binary classification of noisy data. Also, as quantum technology is still insufficient for …

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Flip & Slack – Active Flipped Classroom Learning With Collaborative Slack Interactions, Kyong Jin Shim, Gottipati Swapna, Yi Meng Lau Nov 2021

Flip & Slack – Active Flipped Classroom Learning With Collaborative Slack Interactions, Kyong Jin Shim, Gottipati Swapna, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Active flipped classroom learning is stipulated with faculty structuring the activities involving constructive interactions, either formal or informal. Sharing ideas and responding to ideas improve the cognitive skills of the students. Encouraging peers to contribute to class activities and respecting peers contribute to the development of affective skills. We present an integrated platform for cognitive and affective skills development. A flipped classroom arrangement allows the faculty to focus more on in-class activities such as programming and lab exercises to support active learning in computing courses. We share the design of an innovative flipped classroom model integrated with Slack and present …

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Automating Developer Chat Mining, Shengyi Pan, Lingfeng Bao, Xiaoxue Ren, Xin Xia, David Lo, Shanping Li Nov 2021

Automating Developer Chat Mining, Shengyi Pan, Lingfeng Bao, Xiaoxue Ren, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Online chatrooms are gaining popularity as a communication channel between widely distributed developers of Open Source Software (OSS) projects. Most discussion threads in chatrooms follow a Q&A format, with some developers (askers) raising an initial question and others (respondents) joining in to provide answers. These discussion threads are embedded with rich information that can satisfy the diverse needs of various OSS stakeholders. However, retrieving information from threads is challenging as it requires a thread-level analysis to understand the context. Moreover, the chat data is transient and unstructured, consisting of entangled informal conversations. In this paper, we address this challenge by …

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Incbl: Incremental Bug Localization, Zhou Yang, Jieke Shi, Wang Shaowei, David Lo Nov 2021

Incbl: Incremental Bug Localization, Zhou Yang, Jieke Shi, Wang Shaowei, David Lo

Research Collection School Of Computing and Information Systems

Numerous efforts have been invested in improving the effectiveness of bug localization techniques, whereas little attention is paid to making these tools run more efficiently in continuously evolving software repositories. This paper first analyzes the information retrieval model behind a classic bug localization tool, BugLocator, and builds a mathematical foundation illustrating that the model can be updated incrementally when codebase or bug reports evolve. Then, we present IncBL, a tool for Incremental Bug Localization in evolving software repositories. IncBL is evaluated on the Bugzbook dataset, and the results show that IncBL can significantly reduce the running time by 77.79% on …

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Information Technology And Organizational Learning: Managing Behavioral Change In The Digital Age By Arthur M. Langer, Siu Loon Hoe Nov 2021

Information Technology And Organizational Learning: Managing Behavioral Change In The Digital Age By Arthur M. Langer, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

As the world battles yet another crisis because of the spread of COVID-19, the idea of digitalization brings about a whole new meaning. Many professionals and information technology (IT) managers have remarked that the spread of the coronavirus has accelerated the pace of digital transformation much more so than any effort put forth by C-suite executives. While it is true that most organizations do not accept new technology readily because of embedded legacy systems, changing the corporate cultures does play an important role in affecting the rate of IT adoption. Very often, leaders and senior executives focus on the technological …

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