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Articles 2221 - 2250 of 4271
Full-Text Articles in Entire DC Network
Hierarchical Learning Of Cross-Language Mappings Through Distributed Vector Representations For Code, Nghi D. Q. Bui, Lingxiao Jiang
Hierarchical Learning Of Cross-Language Mappings Through Distributed Vector Representations For Code, Nghi D. Q. Bui, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Translating a program written in one programming language to another can be useful for software development tasks that need functionality implementations in different languages. Although past studies have considered this problem, they may be either specific to the language grammars, or specific to certain kinds of code elements (e.g., tokens, phrases, API uses). This paper proposes a new approach to automatically learn cross-language representations for various kinds of structural code elements that may be used for program translation. Our key idea is two folded: First, we normalize and enrich code token streams with additional structural and semantic information, and train …
Anflo: Detecting Anomalous Sensitive Information Flows In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar
Anflo: Detecting Anomalous Sensitive Information Flows In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar
Research Collection School Of Computing and Information Systems
Smartphone apps usually have access to sensitive user data such as contacts, geo-location, and account credentials and they might share such data to external entities through the Internet or with other apps. Confidentiality of user data could be breached if there are anomalies in the way sensitive data is handled by an app which is vulnerable or malicious. Existing approaches that detect anomalous sensitive data flows have limitations in terms of accuracy because the definition of anomalous flows may differ for different apps with different functionalities; it is normal for “Health” apps to share heart rate information through the Internet …
Exploring Relationship Between Indistinguishability-Based And Unpredictability-Based Rfid Privacy Models, Anjia Yang, Yunhui Zhuang, Jian Weng, Gerhard Hancke, Duncan S. Wong, Guomin Yang
Exploring Relationship Between Indistinguishability-Based And Unpredictability-Based Rfid Privacy Models, Anjia Yang, Yunhui Zhuang, Jian Weng, Gerhard Hancke, Duncan S. Wong, Guomin Yang
Research Collection School Of Computing and Information Systems
A comprehensive privacy model plays a vital role in the design of privacy-preserving RFID authentication protocols. Among various existing RFID privacy models, indistinguishability-based (ind-privacy) and unpredictability-based (unp-privacy) privacy models are the two main categories. Unp*-privacy, a variant of unp-privacy has been claimed to be stronger than ind-privacy. In this paper, we focus on studying RFID privacy models and have three-fold contributions. We start with revisiting unp*-privacy model and figure out a limitation of it by giving a new practical traceability attack which can be proved secure under unp*-privacy model. To capture this kind of attack, we improve unp*-privacy model to …
Analyzing Requirements And Traceability Information To Improve Bug Localization, Michael Rath, David Lo, Patrick Mader
Analyzing Requirements And Traceability Information To Improve Bug Localization, Michael Rath, David Lo, Patrick Mader
Research Collection School Of Computing and Information Systems
Locating bugs in industry-size software systems is time consuming and challenging. An automated approach for assisting the process of tracing from bug descriptions to relevant source code benefits developers. A large body of previous work aims to address this problem and demonstrates considerable achievements. Most existing approaches focus on the key challenge of improving techniques based on textual similarity to identify relevant files. However, there exists a lexical gap between the natural language used to formulate bug reports and the formal source code and its comments. To bridge this gap, state-of-the-art approaches contain a component for analyzing bug history information …
Deep Code Comment Generation, Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin
Deep Code Comment Generation, Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin
Research Collection School Of Computing and Information Systems
During software maintenance, code comments help developerscomprehend programs and reduce additional time spent on readingand navigating source code. Unfortunately, these comments areoften mismatched, missing or outdated in the software projects.Developers have to infer the functionality from the source code.This paper proposes a new approach named DeepCom to automatically generate code comments for Java methods. The generatedcomments aim to help developers understand the functionalityof Java methods. DeepCom applies Natural Language Processing(NLP) techniques to learn from a large code corpus and generatescomments from learned features. We use a deep neural networkthat analyzes structural information of Java methods for bettercomments generation. We conduct …
Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee
Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee
Research Collection School Of Computing and Information Systems
Providing secure access to smart devices such as mobiles, wearables and various other IoT devices is becoming increasinglyimportant, especially as these devices store a range of sensitive personal information. Breathing acoustics-based authentication offers a highly usable and possibly a secondary authentication mechanism for such authorized access, especially as it canbe readily applied to small form-factor devices. Executing sophisticated machine learning pipelines for such authenticationon such devices remains an open problem, given their resource limitations in terms of storage, memory and computational power. To investigate this possibility, we compare the performance of an end-to-end system for both user identification anduser verification …
A Visual Interaction Cue Framework From Video Game Environments For Augmented Reality, Kody R. Dillman, Terrance Tin Hoi Mok, Anthony Tang, Lora Oehlberg, Alex Mitchell
A Visual Interaction Cue Framework From Video Game Environments For Augmented Reality, Kody R. Dillman, Terrance Tin Hoi Mok, Anthony Tang, Lora Oehlberg, Alex Mitchell
Research Collection School Of Computing and Information Systems
Based on an analysis of 49 popular contemporary video games, we develop a descriptive framework of visual interaction cues in video games. These cues are used to inform players what can be interacted with, where to look, and where to go within the game world. These cues vary along three dimensions: the purpose of the cue, the visual design of the cue, and the circumstances under which the cue is shown. We demonstrate that this framework can also be used to describe interaction cues for augmented reality applications. Beyond this, we show how the framework can be used to generatively …
'Is More Better?': Impact Of Multiple Photos On Perception Of Persona Profiles, Joni Salminen, Lene Nielsen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Bernard J. Jansen
'Is More Better?': Impact Of Multiple Photos On Perception Of Persona Profiles, Joni Salminen, Lene Nielsen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
In this research, we investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. We conduct eye-tracking experiments and qualitative interviews with variations in the photos: a single headshot, a headshot and images of the persona in different contexts, and a headshot with pictures of different people representing key persona attributes. The results show that more contextual photos significantly improve the information end users derive from a persona profile; however, showing images of different people creates confusion and lowers the informativeness. Moreover, we discover that choice of pictures results in …
Sehs: Simultaneous Energy Harvesting And Sensing Using Piezoelectric Energy Harvester, Dong Ma, Guohan Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Sehs: Simultaneous Energy Harvesting And Sensing Using Piezoelectric Energy Harvester, Dong Ma, Guohan Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
Piezoelectric energy harvesting (PEH), which converts ambient motion, stress, and vibrations into usable electricity, may help combat battery issues in a growing number of industrial and wearable Internet of things (IoTs). Recently, many works have convincingly demonstrated that PEH can also act as a self-powered sensor for detecting a wide range of machine and human contexts. These developments suggest that the same PEH hardware could be potentially used for simultaneous energy harvesting and sensing (SEHS), offering a new design space for low cost and low power IoT devices. Unfortunately, realization of SEHS is challenging as the energy harvesting process distorts …
Latency-Oriented Task Completion Via Spatial Crowdsourcing, Yuxiang Zeng, Yongxin Tong, Lei Chen, Zimu Zhou
Latency-Oriented Task Completion Via Spatial Crowdsourcing, Yuxiang Zeng, Yongxin Tong, Lei Chen, Zimu Zhou
Research Collection School Of Computing and Information Systems
Spatial crowdsourcing brings in a new approach for social media and location-based services (LBS) to collect locationspecific information via mobile users. For example, when a user checks in at a shop on Facebook, he will immediately receive and is asked to complete a set of tasks such as “what is the opening hour of the shop”. It is non-trivial to complete a set of tasks timely and accurately via spatial crowdsourcing. Since workers in spatial crowdsourcing are often transient and limited in number, these social media platforms need to properly allocate workers within the set of tasks such that all …
Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu
Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu
Research Collection School Of Computing and Information Systems
A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module …
Domain-Specific Cross-Language Relevant Question Retrieval, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Domain-Specific Cross-Language Relevant Question Retrieval, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Chinese developers often cannot effectively search questions in English, because they may have difficulties in translating technical words from Chinese to English and formulating proper English queries. For the purpose of helping Chinese developers take advantage of the rich knowledge base of Stack Overflow and simplify the question retrieval process, we propose an automated cross-language relevant question retrieval (CLRQR) system to retrieve relevant English questions for a given Chinese question. CLRQR first extracts essential information (both Chinese and English) from the title and description of the input Chinese question, then performs domain-specific translation of the essential Chinese information into English, …
Scalable Hypergraph-Based Image Retrieval And Tagging System, Lu Chen, Yunjun Gao, Yuanliang Zhang, Sibo Wang, Baihua Zheng
Scalable Hypergraph-Based Image Retrieval And Tagging System, Lu Chen, Yunjun Gao, Yuanliang Zhang, Sibo Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Massive amounts of images textually annotated by different users are provided by social image websites, e.g., Flickr. Social images are always associated with various information, such as visual features, tags, and users. In this paper, we utilize hypergraph instead of ordinary graph to model social images, since relations among various information are more sophisticated than pairwise. Based on the hypergraph, we propose HIRT, a scalable image retrieval and tagging system, which uses Personalized PageRank to measure vertex similarity, and employs top-k search to support image retrieval and tagging. To achieve good scalability and efficiency, we develop parallel and approximate top-k …
Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
To facilitate developers in effective allocation of their testing and debugging efforts, many software defect prediction techniques have been proposed in the literature. These techniques can be used to predict classes that are more likely to be buggy based on the past history of classes, methods, or certain other code elements. These techniques are effective provided that a sufficient amount of data is available to train a prediction model. However, sufficient training data are rarely available for new software projects. To resolve this problem, cross-project defect prediction, which transfers a prediction model trained using data from one project to another, …
Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
To help developers better allocate testing and debugging efforts, many software defect prediction techniques have been proposed in the literature. These techniques can be used to predict classes that are more likely to be buggy based on past history of buggy classes. These techniques work well as long as a sufficient amount of data is available to train a prediction model. However, there is rarely enough training data for new software projects. To deal with this problem, cross-project defect prediction, which transfers a prediction model trained using data from one project to another, has been proposed and is regarded as …
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shaowei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shaowei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Software engineers share experiences with modern technologies by means of software information sites, such as Stack Overflow. These sites allow developers to label posted content, referred to as software objects, with short descriptions, known as tags. However, tags assigned to objects tend to be noisy and some objects are not well tagged. To improve the quality of tags in software information sites, we propose EnTagRec, an automatic tag recommender based on historical tag assignments to software objects and we evaluate its performance on four software information sites, Stack Overflow, Ask Ubuntu, Ask Different, and Free code. We observe that that …
Deeprefiner: Multi-Layer Android Malware Detection System Applying Deep Neural Networks, Xu Ke, Yingjiu Li, Robert H. Deng, Kai Chen
Deeprefiner: Multi-Layer Android Malware Detection System Applying Deep Neural Networks, Xu Ke, Yingjiu Li, Robert H. Deng, Kai Chen
Research Collection School Of Computing and Information Systems
As malicious behaviors vary significantly across mobile malware, it is challenging to detect malware both efficiently and effectively. Also due to the continuous evolution of malicious behaviors, it is difficult to extract features by laborious human feature engineering and keep up with the speed of malware evolution. To solve these challenges, we propose DeepRefiner to identify malware both efficiently and effectively. The novel technique enabling effectiveness is the semantic-based deep learning. We use Long Short Term Memory on the semantic structure of Android bytecode, avoiding missing the details of method-level bytecode semantics. To achieve efficiency, we apply Multilayer Perceptron on …
Empirical Study Of Face Authentication Systems Under Osnfd Attacks, Yan Li, Yingjiu Li, Xu, Ke, Qiang Yan, Robert H. Deng
Empirical Study Of Face Authentication Systems Under Osnfd Attacks, Yan Li, Yingjiu Li, Xu, Ke, Qiang Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Face authentication has been widely available on smartphones, tablets, and laptops. As numerous personal images are published in online social networks (OSNs), OSN-based facial disclosure (OSNFD) creates significant threat against face authentication. We make the first attempt to quantitatively measure OSNFD threat to real-world face authentication systems on smartphones, tablets, and laptops. Our results show that the percentage of vulnerable users that are subject to spoofing attacks is high, which is about 64% for laptop users, and 93% smartphone/tablet users. We investigate liveness detection methods in the real-world face authentication systems against OSNFD threat. We discover that under protection of …
Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li
Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li
Research Collection School Of Computing and Information Systems
Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …
Introducing Basic Programming To Pre-University Students: A Successful Initiative In Singapore, Heng Ngee Mok, Vandana Ramachandra Rao
Introducing Basic Programming To Pre-University Students: A Successful Initiative In Singapore, Heng Ngee Mok, Vandana Ramachandra Rao
Research Collection School Of Computing and Information Systems
“Let’s Code!” is an intensive 3-week basic programming course that aims to formally expose pre-university students in Singapore to programming. This course was conducted in blended-learning format, and included lecture videos, self-check quizzes, video conferences, meet-up tutorials and take-home programming assignments. The authors hope to capture the experience gained from running this course for educators who intend to implement similar courses in the future. Besides a detailed description of this course, significant changes that were made based on feedback from participants and members of the teaching team are documented here.
Vocal Programming For People With Upper-Body Motor Impairments, Lucas Rosenblatt, Patrick Carrington, Kotaro Hara, Jeffrey P. Bigham
Vocal Programming For People With Upper-Body Motor Impairments, Lucas Rosenblatt, Patrick Carrington, Kotaro Hara, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
Programming heavily relies on entering text using traditional QWERTY keyboards, which poses challenges for people with limited upper-body movement. Developing tools using a publicly available speech recognition API could provide a basis for keyboard free programming. In this paper, we describe our efforts in design, development, and evaluation of a voice-based IDE to support people with limited dexterity.
Sok: Towards The Science Of Security And Privacy In Machine Learning, Nicolas Papernot, Patrick Mcdaniel, Arunesh Sinha, Michael Wellman
Sok: Towards The Science Of Security And Privacy In Machine Learning, Nicolas Papernot, Patrick Mcdaniel, Arunesh Sinha, Michael Wellman
Research Collection School Of Computing and Information Systems
Advances in machine learning (ML) in recent years have enabled a dizzying array of applications such as data analytics, autonomous systems, and security diagnostics. ML is now pervasive—new systems and models are being deployed in every domain imaginable, leading to rapid and widespread deployment of software based inference and decision making. There is growing recognition that ML exposes new vulnerabilities in software systems, yet the technical community’s understanding of the nature and extent of these vulnerabilities remains limited. We systematize recent findings on ML security and privacy, focusing on attacks identified on these systems and defenses crafted to date. We …
Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame
Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame
Research Collection School Of Computing and Information Systems
Context: Modern internet-based services, ranging from food-delivery to home-caring, leverage the availability of multiple programmable devices to provide handy services tailored to end-user needs. These services are delivered through an ecosystem of device-specific software components and interfaces (e.g., mobile and wearable device applications). Since they often handle private information (e.g., location and health status), their security and privacy requirements are of crucial importance. Defining and analyzing those requirements is a significant challenge due to the multiple types of software components and devices integrated into software ecosystems. Each software component presents peculiarities that often depend on the context and the devices …
The Impact Of Rapid Release Cycles On The Integration Delay Of Fixed Issues, Daniel Alencar Da Costa, Shane Mcintosh, Christoph Treude, Uirá Kulesza, Ahmed E. Hassan
The Impact Of Rapid Release Cycles On The Integration Delay Of Fixed Issues, Daniel Alencar Da Costa, Shane Mcintosh, Christoph Treude, Uirá Kulesza, Ahmed E. Hassan
Research Collection School Of Computing and Information Systems
The release frequency of software projects has increased in recent years. Adopters of so-called rapid releases—short release cycles, often on the order of weeks, days, or even hours—claim that they can deliver fixed issues (i.e., implemented bug fixes and new features) to users more quickly. However, there is little empirical evidence to support these claims. In fact, our prior work shows that code integration phases may introduce delays for rapidly releasing projects—98% of the fixed issues in the rapidly releasing Firefox project had their integration delayed by at least one release. To better understand the impact that rapid release cycles …
Regularly Lossy Functions And Applications, Yu Chen, Baodong Qin, Haiyang Xue
Regularly Lossy Functions And Applications, Yu Chen, Baodong Qin, Haiyang Xue
Research Collection School Of Computing and Information Systems
In STOC 2008, Peikert and Waters introduced a powerful primitive called lossy trapdoor functions (LTFs). In a nutshell, LTFs are functions that behave in one of two modes. In the normal mode, functions are injective and invertible with a trapdoor. In the lossy mode, functions statistically lose information about their inputs. Moreover, the two modes are computationally indistinguishable. In this work, we put forward a relaxation of LTFs, namely, regularly lossy functions (RLFs). Compared to LTFs, the functions in the normal mode are not required to be efficiently invertible or even unnecessary to be injective. Instead, they could also be …
Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani
Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani
Research Collection School Of Computing and Information Systems
Selecting an item of interest on smartwatches can be tedious and time-consuming as it involves a series of swipe and tap actions. We present PageFlip, a novel method that combines into a single action multiple touch operations such as command invocation and value selection for efficient interaction on smartwatches. PageFlip operates with a page flip gesture that starts by dragging the UI from a corner of the device. We first design PageFlip by examining its key design factors such as corners, drag directions and drag distances. We next compare PageFlip to a functionally equivalent radial menu and a standard swipe …
Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo
Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo
Research Collection School Of Computing and Information Systems
We present a new type of public-key encryption called Criteria-based Encryption (or , for short). Different from Attribute-based Encryption, in , we consider the access policies as criteria carrying different weights. A user must hold some cases (or answers) satisfying the criteria and have sufficient weights in order to successfully decrypt a message. We then propose two Schemes under different settings: the first scheme requires a user to have at least one case for a criterion specified by the encryptor in the access structure, while the second scheme requires a user to have all the cases for each criterion. We …
Geocaching With A Beam: Shared Outdoor Activities Through A Telepresence Robot With 360 Degree Viewing, Yasamin Heshmat, Brennan Jones, Xiaoxuan Xiong, Carman Neustaedter, Anthony Tang, Bernhard E. Riecke, Lillian Yang
Geocaching With A Beam: Shared Outdoor Activities Through A Telepresence Robot With 360 Degree Viewing, Yasamin Heshmat, Brennan Jones, Xiaoxuan Xiong, Carman Neustaedter, Anthony Tang, Bernhard E. Riecke, Lillian Yang
Research Collection School Of Computing and Information Systems
People often enjoy sharing outdoor activities together such as walking and hiking. However, when family and friends are separated by distance it can be difficult if not impossible to share such activities. We explore this design space by investigating the benefits and challenges of using a telepresence robot to support outdoor leisure activities. In our study, participants participated in the outdoor activity of geocaching where one person geocached with the help of a remote partner via a telepresence robot. We compared a wide field of view (WFOV) camera to a 360° camera. Results show the benefits of having a physical …
Perspective On And Re-Orientation Of Physical Proxies In Object-Focused Remote Collaboration, Martin Feick, Terrance Mok, Anthony Tang, Lora Oehlberg, Ehud Sharlin
Perspective On And Re-Orientation Of Physical Proxies In Object-Focused Remote Collaboration, Martin Feick, Terrance Mok, Anthony Tang, Lora Oehlberg, Ehud Sharlin
Research Collection School Of Computing and Information Systems
Remote collaborators working together on physical objects have difficulty building a shared understanding of what each person is talking about. Conventional video chat systems are insufficient for many situations because they present a single view of the object in a flattened image. To understand how this limited perspective affects collaboration, we designed the Remote Manipulator (ReMa), which can reproduce orientation manipulations on a proxy object at a remote site. We conducted two studies with ReMa, with two main findings. First, a shared perspective is more effective and preferred compared to the opposing perspective offered by conventional video chat systems. Second, …
A Utp Semantics For Communicating Processes With Shared Variables And Its Formal Encoding In Pvs, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin
A Utp Semantics For Communicating Processes With Shared Variables And Its Formal Encoding In Pvs, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin
Research Collection School Of Computing and Information Systems
CSP# (communicating sequential programs) is a modelling language designed for specifying concurrent systems by integrating CSP-like compositional operators with sequential programs updating shared variables. In this work, we define an observation-oriented denotational semantics in an open environment for the CSP# language based on the UTP framework. To deal with shared variables, we lift traditional event-based traces into mixed traces which consist of state-event pairs for recording process behaviours. To capture all possible concurrency behaviours between action/channel-based communications and global shared variables, we construct a comprehensive set of rules on merging traces from processes which run in parallel/interleaving. We also define …