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Articles 1441 - 1470 of 4315
Full-Text Articles in Computer Sciences
Erica: Enabling Real-Time Mistake Detection And Corrective Feedback For Free-Weights Exercises, Meeralakshmi Radhakrishnan, Darshana Rathnayake, Koon Han Ong, Inseok Hwang, Archan Misra
Erica: Enabling Real-Time Mistake Detection And Corrective Feedback For Free-Weights Exercises, Meeralakshmi Radhakrishnan, Darshana Rathnayake, Koon Han Ong, Inseok Hwang, Archan Misra
Research Collection School Of Computing and Information Systems
We present ERICA, a digital personal trainer for users performing free weights exercises, with two key differentiators: (a) First, unlike prior approaches that either require multiple on-body wearables or specialized infrastructural sensing, ERICA uses a single in-ear "earable" device (piggybacking on a form factor routinely used by millions of gym-goers) and a simple inertial sensor mounted on each weight equipment; (b) Second, unlike prior work that focuses primarily on quantifying a workout, ERICA additionally identifies a variety of fine-grained exercising mistakes and delivers real-time, in-situ corrective instructions. To achieve this, we (a) design a robust approach for user-equipment association that …
Effort-Aware Just-In-Time Defect Identification In Practice: A Case Study At Alibaba, Meng Yan, Xin Xia, Yuanrui Fan, David Lo, Ahmed E. Hassan, Xindong Zhang
Effort-Aware Just-In-Time Defect Identification In Practice: A Case Study At Alibaba, Meng Yan, Xin Xia, Yuanrui Fan, David Lo, Ahmed E. Hassan, Xindong Zhang
Research Collection School Of Computing and Information Systems
Effort-aware Just-in-Time (JIT) defect identification aims at identifying defect-introducing changes just-in-time with limited code inspection effort. Such identification has two benefits compared with traditional module-level defect identification, i.e., identifying defects in a more cost-effective and efficient manner. Recently, researchers have proposed various effort-aware JIT defect identification approaches, including supervised (e.g., CBS+, OneWay) and unsupervised approaches (e.g., LT and Code Churn). The comparison of the effectiveness between such supervised and unsupervised approaches has attracted a large amount of research interest. However, the effectiveness of the recently proposed approaches and the comparison among them have never been investigated in an industrial setting.In …
Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker
Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker
Research Collection School Of Computing and Information Systems
Android as an operating system is now increasingly being adopted in industrial information systems, especially with Cyber-Physical Systems (CPS). This also puts Android devices onto the front line of handling security-related data and conducting sensitive behaviors, which could be misused by the increasing number of polymorphic and metamorphic malicous applications targeting the platform. The existence of such malware threats therefore call for more accurate identification and surveillance of sensitive Android app behaviors, which is essential to the security of CPS and IoT devices powered by Android. Nevertheless, achieving dynamic app behavior monitoring and identification on real CPS powered by Android …
Api Method Recommendation Via Explicit Matching Of Functionality Verb Phrases, Wenkai Xie, Xin Peng, Mingwei Liu, Christoph Treude, Zhenchang Xing, Xiaoxin Zhang, Wenyun Zhao
Api Method Recommendation Via Explicit Matching Of Functionality Verb Phrases, Wenkai Xie, Xin Peng, Mingwei Liu, Christoph Treude, Zhenchang Xing, Xiaoxin Zhang, Wenyun Zhao
Research Collection School Of Computing and Information Systems
Due to the lexical gap between functionality descriptions and user queries, documentation-based API retrieval often produces poor results. Verb phrases and their phrase patterns are essential in both describing API functionalities and interpreting user queries. Thus we hypothesize that API retrieval can be facilitated by explicitly recognizing and matching between the fine-grained structures of functionality descriptions and user queries. To verify this hypothesis, we conducted a large-scale empirical study on the functionality descriptions of 14,733 JDK and Android API methods. We identified 356 different functionality verbs from the descriptions, which were grouped into 87 functionality categories, and we extracted 523 …
Bugsinpy: A Database Of Existing Bugs In Python Programs To Enable Controlled Testing And Debugging Studies, Ratnadira Widyasari, Sheng Qin Sim, Camellia Lok, Haodi Qi, Jack Phan, Qijin Tay, Constance Tan, Fiona Wee, Jodie Ethelda Tan, Yuheng Yieh, Brian Goh, Ferdian Thung, Hong Jin Kang, Thong Hoang, David Lo, Eng Lieh Ouh
Bugsinpy: A Database Of Existing Bugs In Python Programs To Enable Controlled Testing And Debugging Studies, Ratnadira Widyasari, Sheng Qin Sim, Camellia Lok, Haodi Qi, Jack Phan, Qijin Tay, Constance Tan, Fiona Wee, Jodie Ethelda Tan, Yuheng Yieh, Brian Goh, Ferdian Thung, Hong Jin Kang, Thong Hoang, David Lo, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
The 2019 edition of Stack Overflow developer survey highlights that, for the first time, Python outperformed Java in terms of popularity. The gap between Python and Java further widened in the 2020 edition of the survey. Unfortunately, despite the rapid increase in Python's popularity, there are not many testing and debugging tools that are designed for Python. This is in stark contrast with the abundance of testing and debugging tools for Java. Thus, there is a need to push research on tools that can help Python developers.One factor that contributed to the rapid growth of Java testing and debugging tools …
Deepcommenter: A Deep Code Comment Generation Tool With Hybrid Lexical And Syntactical Information, Boao Li, Meng Yan, Xin Xia, Xing Hu, Ge Li, David Lo
Deepcommenter: A Deep Code Comment Generation Tool With Hybrid Lexical And Syntactical Information, Boao Li, Meng Yan, Xin Xia, Xing Hu, Ge Li, David Lo
Research Collection School Of Computing and Information Systems
As the scale of software projects increases, the code comments are more and more important for program comprehension. Unfortunately, many code comments are missing, mismatched or outdated due to tight development schedule or other reasons. Automatic code comment generation is of great help for developers to comprehend source code and reduce their workload. Thus, we propose a code comment generation tool (DeepCommenter) to generate descriptive comments for Java methods. DeepCommenter formulates the comment generation task as a machine translation problem and exploits a deep neural network that combines the lexical and structural information of Java methods. We implement DeepCommenter in …
Coinwatch: A Clone-Based Approach For Detecting Vulnerabilities In Cryptocurrencies, Qingze Hum, Wei Jin Tan, Shi Ying Tey, Latasha Lenus, Ivan Homoliak, Yun Lin, Jun Sun
Coinwatch: A Clone-Based Approach For Detecting Vulnerabilities In Cryptocurrencies, Qingze Hum, Wei Jin Tan, Shi Ying Tey, Latasha Lenus, Ivan Homoliak, Yun Lin, Jun Sun
Research Collection School Of Computing and Information Systems
Cryptocurrencies have become very popular in recent years. Thousands of new cryptocurrencies have emerged, proposing new and novel techniques that improve on Bitcoin's core innovation of the blockchain data structure and consensus mechanism. However, cryptocurrencies are a major target for cyber-attacks, as they can be sold on exchanges anonymously and most cryptocurrencies have their codebases publicly available. One particular issue is the prevalence of code clones in cryptocurrencies, which may amplify security threats. If a vulnerability is found in one cryptocurrency, it might be propagated into other cloned cryptocurrencies. In this work, we propose a systematic remedy to this problem, …
A Theory Of The Engagement In Open Source Projects Via Summer Of Code Programs, Jefferson Silva, Igor Wiese, Daniel M. German, Christoph Treude, Marco A. Gerosa, Igor Steinmacher
A Theory Of The Engagement In Open Source Projects Via Summer Of Code Programs, Jefferson Silva, Igor Wiese, Daniel M. German, Christoph Treude, Marco A. Gerosa, Igor Steinmacher
Research Collection School Of Computing and Information Systems
Summer of code programs connect students to open source software (OSS) projects, typically during the summer break from school. Analyzing consolidated summer of code programs can reveal how college students, who these programs usually target, can be motivated to participate in OSS, and what onboarding strategies OSS communities adopt to receive these students. In this paper, we study the well-established Google Summer of Code (GSoC) and devise an integrated engagement theory grounded in multiple data sources to explain motivation and onboarding in this context. Our analysis shows that OSS communities employ several strategies for planning and executing student participation, socially …
Perceptions, Expectations, And Challenges In Defect Prediction, Zhiyuan Wan, Xin Xia, Ahmed E. Hassan, David Lo, Jianwei Yin, Xiaohu Yang
Perceptions, Expectations, And Challenges In Defect Prediction, Zhiyuan Wan, Xin Xia, Ahmed E. Hassan, David Lo, Jianwei Yin, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Defect prediction has been an active research area for over four decades. Despite numerous studies on defect prediction, the potential value of defect prediction in practice remains unclear. To address this issue, we performed a mixed qualitative and quantitative study to investigate what practitioners think, behave and expect in contrast to research findings when it comes to defect prediction. We collected hypotheses from open-ended interviews and a literature review, followed by a validation survey. We received 395 responses from practitioners. Some of our key findings include: 1) Over 90% of respondents are willing to adopt defect prediction techniques. 2) There …
Sfuzz: An Efficient Adaptive Fuzzer For Solidity Smart Contracts, Tai D. Nguyen, Long H. Pham, Jun Sun, Yun Lin, Minh Quang Tran
Sfuzz: An Efficient Adaptive Fuzzer For Solidity Smart Contracts, Tai D. Nguyen, Long H. Pham, Jun Sun, Yun Lin, Minh Quang Tran
Research Collection School Of Computing and Information Systems
Smart contracts are Turing-complete programs that execute on the infrastructure of the blockchain, which often manage valuable digital assets. Solidity is one of the most popular programming languages for writing smart contracts on the Ethereum platform. Like traditional programs, smart contracts may contain vulnerabilities. Unlike traditional programs, smart contracts cannot be easily patched once they are deployed. It is thus important that smart contracts are tested thoroughly before deployment. In this work, we present an adaptive fuzzer for smart contracts on the Ethereum platform called sFuzz. Compared to existing Solidity fuzzers, sFuzz combines the strategy in the AFL fuzzer and …
Jito: A Tool For Just-In-Time Defect Identification And Localization, Fangcheng Qiu, Meng Yan, Xin Xia, Xinyu Wang, Yuanrui Fan, Ahmed E. Hassan, David Lo
Jito: A Tool For Just-In-Time Defect Identification And Localization, Fangcheng Qiu, Meng Yan, Xin Xia, Xinyu Wang, Yuanrui Fan, Ahmed E. Hassan, David Lo
Research Collection School Of Computing and Information Systems
In software development and maintenance, defect localization is necessary for software quality assurance. Current defect localization techniques mainly rely on defect symptoms (e.g., bug reports or program spectrum) when the defect has been exposed. One challenge task is: can we locate buggy program prior to the appearance of the defect symptom. Such kind of localization is conducted at an early stage (e.g., when buggy program elements are being checkedin) which can be an early step of continuous quality control.In this paper, we propose a Just-In-Time defect identification and lOcalization tool, named JITO, which can help developers to locate defective lines …
Enhancing Developer Interactions With Programming Screencasts Through Accurate Code Extraction, Lingfeng Bao, Shengyi Pan, Zhenchang Xing, Xin Xia, David Lo, Xiaohu Yang
Enhancing Developer Interactions With Programming Screencasts Through Accurate Code Extraction, Lingfeng Bao, Shengyi Pan, Zhenchang Xing, Xin Xia, David Lo, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code.In this paper, we develop a tool named psc2code, which has two components, …
Reducing Estimation Bias Via Triplet-Average Deep Deterministic Policy Gradient, Dongming Wu, Xingping Dong, Jianbing Shen, Steven C. H. Hoi
Reducing Estimation Bias Via Triplet-Average Deep Deterministic Policy Gradient, Dongming Wu, Xingping Dong, Jianbing Shen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The overestimation caused by function approximation is a well-known property in Q-learning algorithms, especially in single-critic models, which leads to poor performance in practical tasks. However, the opposite property, underestimation, which often occurs in Q-learning methods with double critics, has been largely left untouched. In this article, we investigate the underestimation phenomenon in the recent twin delay deep deterministic actor-critic algorithm and theoretically demonstrate its existence. We also observe that this underestimation bias does indeed hurt performance in various experiments. Considering the opposite properties of single-critic and double-critic methods, we propose a novel triplet-average deep deterministic policy gradient algorithm that …
An Empirical Study Of Release Note Production And Usage In Practice, Tingting Bi, Xin Xia, David Lo, John Grundy, Thomas Zimmermann
An Empirical Study Of Release Note Production And Usage In Practice, Tingting Bi, Xin Xia, David Lo, John Grundy, Thomas Zimmermann
Research Collection School Of Computing and Information Systems
The release note is one of the most important software artifacts that serves as a bridge for communication among stakeholders. Release notes contain a set of crucial information, such as descriptions of enhancements, improvements, potential issues, development, evolution, testing, and maintenance of projects throughout the whole development lifestyle. A comprehensive understanding of what makes a good release note and how to write one for different stakeholders would be highly beneficial. However, in practice, the release note is often neglected by stakeholders and has not to date been systematically investigated by researchers. In this paper, we conduct a mixed methods study …
Selecting Third-Party Libraries: The Practitioners' Perspective, Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousios
Selecting Third-Party Libraries: The Practitioners' Perspective, Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousios
Research Collection School Of Computing and Information Systems
The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software project in terms of cost, time, and development effort, with the severity of the impact depending on the role of the library in the software architecture, among others. Despite the importance of following a careful library selection process, in practice, the selection of third-party libraries is still conducted in an ad-hoc manner, where dozens of factors play an influential role in the decision. In this …
"Authors On The Hill " Presents Prof. Giovanni Spani, Giovanni Spani
"Authors On The Hill " Presents Prof. Giovanni Spani, Giovanni Spani
Authors on the Hill
Professor Giovanni Spani of the World Languages, Literatures, and Cultures Department at the College of the Holy Cross will present his work on Dante's Florence, a multimedia educational app for Android and iOS.
Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari
Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari
Department of Computer Science Faculty Scholarship and Creative Works
With the rapid growth of smart devices and technological advancements in tracking geospatial data, the demand for Location-Based Services (LBS) is facing a constant rise in several domains, including military, healthcare and transportation. It is a natural step to migrate LBS to a cloud environment to achieve on-demand scalability and increased resiliency. Nonetheless, outsourcing sensitive location data to a third-party cloud provider raises a host of privacy concerns as the data owners have reduced visibility and control over the outsourced data. In this paper, we consider outsourced LBS where users want to retrieve map directions without disclosing their location information. …
Enhancing A Cluster-Based Tdma Mac Protocol For Vehicle-To-Vehicle Communications, Abubakar Bello Tambawal
Enhancing A Cluster-Based Tdma Mac Protocol For Vehicle-To-Vehicle Communications, Abubakar Bello Tambawal
Student Works (2020-2029)
Vehicular Ad hoc Network technology (VANET) is one of the emerging and promising wireless technology, providing support for vehicles to communicate and share resources, (such as safety messages) through vehicle-to-vehicle (V2V) communications. Sequel to that the Time Division Multiple Access (TDMA) MAC protocol using a cluster-based topology has been proposed by the research community. Most of the existing research works focused on the cluster head (CH) election with very few addressing other critical issues, including cluster formation, efficient time slot allocation, and cluster maintenance. These challenges result in an unstable cluster, which could affect the timely delivery of safety applications. …
Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu
Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu
Research Collection School Of Computing and Information Systems
With the recent advances in voice synthesis, AI-synthesized fake voices are indistinguishable to human ears and widely are applied to produce realistic and natural DeepFakes, exhibiting real threats to our society. However, effective and robust detectors for synthesized fake voices are still in their infancy and are not ready to fully tackle this emerging threat. In this paper, we devise a novel approach, named DeepSonar, based on monitoring neuron behaviors of speaker recognition (SR) system, i.e., a deep neural network (DNN), to discern AI-synthesized fake voices. Layer-wise neuron behaviors provide an important insight to meticulously catch the differences among inputs, …
Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara
Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara
Research Collection School Of Computing and Information Systems
We transform traditional experience writing into in-situ voice-based multimedia authoring. Documenting experiences digitally in blogs and journals is a common activity that allows people to socially connect with others by sharing their experiences (e.g. travelogue). However, documenting such experiences can be time-consuming and cognitively demanding as it is typically done OUT-OF-CONTEXT (after the actual experience). We propose in-situ voice-based multimedia authoring (IVA), an alternative workflow to allow IN-CONTEXT experience documentation. Unlike the traditional approach, IVA encourages in-context content creations using voice-based multimedia input and stores them in multi-modal "snippets". The snippets can be rearranged to form multimedia articles and can …
Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta
Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta
Research Collection School Of Computing and Information Systems
Combining video streaming and online retailing (V2R) has been a growing trend recently. In this paper, we provide practitioners and researchers in multimedia with a cloud-based platform named Hysia for easy development and deployment of V2R applications. The system consists of: 1) a back-end infrastructure providing optimized V2R related services including data engine, model repository, model serving and content matching; and 2) an application layer which enables rapid V2R application prototyping. Hysia addresses industry and academic needs in large-scale multimedia by: 1) seamlessly integrating state-of-the-art libraries including NVIDIA video SDK, Facebook faiss, and gRPC; 2) efficiently utilizing GPU computation; and …
White-Box Fairness Testing Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Dai Ting
White-Box Fairness Testing Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Dai Ting
Research Collection School Of Computing and Information Systems
Although deep neural networks (DNNs) have demonstrated astonishing performance in many applications, there are still concerns on their dependability. One desirable property of DNN for applications with societal impact is fairness (i.e., non-discrimination). In this work, we propose a scalable approach for searching individual discriminatory instances of DNN. Compared with state-of-the-art methods, our approach only employs lightweight procedures like gradient computation and clustering, which makes it significantly more scalable than existing methods. Experimental results show that our approach explores the search space more effectively (9 times) and generates much more individual discriminatory instances (25 times) using much less time (half …
Iot-Enabled Community Care For Ageing-In-Place: The Singapore Experience, Hwee-Pink Tan
Iot-Enabled Community Care For Ageing-In-Place: The Singapore Experience, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
The paradigm of ageing-in-place – where the elderly live and age in their own homes, independently and safely, with care provided by the community – is compelling, especially in societies that face both shortages in institutionalized eldercare resources, and rapidly ageing populations. When the number of elderly who live alone rises rapidly, support and care from their communities become increasing crucial. Internet of Things (IoT) technologies. They can become the fundamental enabler for smart community eldercare. In this presentation, I would like to share our experiences and learnings gathered from large-scale deployments of IoT systems in in-home and community spaces …
Evaluating Methods For Students To Identify And Clarify Doubts In Computing Design Courses, Eng Lieh Ouh, Benjamin Gan
Evaluating Methods For Students To Identify And Clarify Doubts In Computing Design Courses, Eng Lieh Ouh, Benjamin Gan
Research Collection School Of Computing and Information Systems
This full paper evaluates the effectiveness of doubts identification and clarification methods applied in undergraduate computing design courses. Many undergraduate courses in computing require students to understand abstract design concepts. Exposed to the design concepts for the first time, students need to be able to identify and clarify their doubts about the abstract concepts in order to make the right design decisions. In this study, we seek to evaluate the effectiveness of six methods that help students to identify and clarify their doubts. These methods vary in their timing (immediate or delayed), communication style (online or face-to-face) and participation style …
A Critical Genre Analysis Of The User Requirement Specification Report In The Information Technology Industry, Shahizan Shaharuddin
A Critical Genre Analysis Of The User Requirement Specification Report In The Information Technology Industry, Shahizan Shaharuddin
Student Works (2020-2029)
While it has been established that discursive practices involving writing are highly situated and context-bound, few local studies have examined the processes involved in the construction of texts and the shaping of the intended text. Recent perspectives on writing as ways of working and acting, and texts as social action suggest that studying the processes behind the construction of a text could provide a clearer understanding of the discursive practices involved in the shaping of the text. This is seen as relevant to professional writing context in the present study as texts are often shaped to facilitate the social action …
Deeprhythm: Exposing Deepfakes With Attentional Visual Heartbeat Rhythms, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao
Deeprhythm: Exposing Deepfakes With Attentional Visual Heartbeat Rhythms, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao
Research Collection School Of Computing and Information Systems
As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors. Motivated by the fact that remote visual photoplethysmography (PPG) is made possible by monitoring the minuscule periodic changes of skin color due to blood pumping through the face, we conjecture that normal heartbeat rhythms found in the real face videos will be disrupted or even entirely broken in a DeepFake video, making it a potentially powerful indicator for DeepFake detection. In this work, we propose DeepRhythm, a DeepFake …
Sentiment Analysis For Software Engineering: How Far Can Pre-Trained Transformer Models Go?, Ting Zhang, Bowen Xu, Thung Ferdian, Stefanus Agus Haryono, David Lo, Lingxiao Jiang
Sentiment Analysis For Software Engineering: How Far Can Pre-Trained Transformer Models Go?, Ting Zhang, Bowen Xu, Thung Ferdian, Stefanus Agus Haryono, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Extensive research has been conducted on sentiment analysis for software engineering (SA4SE). Researchers have invested much effort in developing customized tools (e.g., SentiStrength-SE, SentiCR) to classify the sentiment polarity for Software Engineering (SE) specific contents (e.g., discussions in Stack Overflow and code review comments). Even so, there is still much room for improvement. Recently, pre-trained Transformer-based models (e.g., BERT, XLNet) have brought considerable breakthroughs in the field of natural language processing (NLP). In this work, we conducted a systematic evaluation of five existing SA4SE tools and variants of four state-of-the-art pre-trained Transformer-based models on six SE datasets. Our work is …
Efficient Ciphertext-Policy Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Jiaming Yuan, Guowen Xu, Yingjiu Li, Ximeng Liu, Yinghui Zhang, Zuobin Yang
Efficient Ciphertext-Policy Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Jiaming Yuan, Guowen Xu, Yingjiu Li, Ximeng Liu, Yinghui Zhang, Zuobin Yang
Research Collection School Of Computing and Information Systems
Traitor tracing scheme is a paradigm to classify the users who illegal use of their decryption keys in cryptosystems. In the ciphertext-policy attribute-based cryptosystem, the decryption key usually contains the users’ attributes, while the real identities are hidden. The decryption key with hidden identities enables malicious users to intentionally leak decryption keys or embed the decryption keys in the decryption device to gain illegal profits with a little risk of being discovered. To mitigate this problem, the concept of blackbox traceability in the ciphertext-policy attribute-based scheme was proposed to identify the malicious user via observing the I/O streams of the …
Message From The General Co-Chairs And The Program Co-Chairs, Christoph Treude, Hongyu Zhang, Kelly Blincoe, Zhenchang Xing
Message From The General Co-Chairs And The Program Co-Chairs, Christoph Treude, Hongyu Zhang, Kelly Blincoe, Zhenchang Xing
Research Collection School Of Computing and Information Systems
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney
Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney
Articles
The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …