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Articles 1 - 30 of 86
Full-Text Articles in Physical Sciences and Mathematics
Fundamental Limits On End-To-End Throughput Of Network Coding In Multi-Rate And Multicast Wireless Networks, Luiz Felipe Viera, Mario Gerla, Archan Misra
Fundamental Limits On End-To-End Throughput Of Network Coding In Multi-Rate And Multicast Wireless Networks, Luiz Felipe Viera, Mario Gerla, Archan Misra
Research Collection School Of Computing and Information Systems
This paper investigates the interaction between network coding and link-layer transmission rate diversity in multi-hop wireless networks. By appropriately mixing data packets at intermediate nodes, network coding allows a single multicast flow to achieve higher throughput to a set of receivers. Broadcast applications can also exploit link-layer rate diversity, whereby individual nodes can transmit at faster rates at the expense of corresponding smaller coverage area. We first demonstrate how combining rate-diversity with network coding can provide a larger capacity for data dissemination of a single multicast flow, and how consideration of rate diversity is critical for maximizing system throughput. Next …
Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin
Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin
Research Collection School Of Computing and Information Systems
This paper addresses the difficult problem of finding dense correspondence across images with large appearance variations. Our method uses multiple feature samples at each pixel to deal with the appearance variations based on our observation that pre-defined single feature sample provides poor results in nearest neighbor matching. We apply the idea in a flow-based matching framework and utilize the best feature sample for each pixel to determine the flow field. We propose a novel energy function and use dual-layer loopy belief propagation to minimize it where the correspondence, the feature scale and rotation parameters are solved simultaneously. Our method is …
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Research Collection School Of Computing and Information Systems
Crowdsourcing platforms such as Amazon Mechanical Turk and Google Consumer Surveys can profile users based on their inputs to online surveys. In this work we first demonstrate how easily user privacy can be compromised by collating information from multiple surveys. We then propose, develop, and evaluate a crowdsourcing survey platform called Loki that allows users to control their privacy loss via atsource obfuscation.
Towards A Hybrid Framework For Detecting Input Manipulation Vulnerabilities, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
Towards A Hybrid Framework For Detecting Input Manipulation Vulnerabilities, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
Research Collection School Of Computing and Information Systems
Input manipulation vulnerabilities such as SQL Injection, Cross-site scripting, Buffer Overflow vulnerabilities are highly prevalent and pose critical security risks. As a result, many methods have been proposed to apply static analysis, dynamic analysis or a combination of them, to detect such security vulnerabilities. Most of the existing methods classify vulnerabilities into safe and unsafe. They have both false-positive and false-negative cases. In general, security vulnerability can be classified into three cases: (1) provable safe, (2) provable unsafe, (3) unsure. In this paper, we propose a hybrid framework-Detecting Input Manipulation Vulnerabilities (DIMV), to verify the adequacy of security vulnerability defenses …
Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar
Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar
Research Collection School Of Computing and Information Systems
Research into software engineering (SE) education is largely concentrated on teaching and learning issues in coursework programs. This paper, in contrast, provides a meta analysis of research publications in software engineering to help with research education in SE. Studying publication patterns in a discipline will assist research students and supervisors gain a deeper understanding of how successful research has occurred in the discipline. We present results from a large scale empirical study covering over three and a half decades of software engineering research publications. We identify how different factors of publishing relate to the number of papers published as well …
Automatic Recommendation Of Api Methods From Feature Requests, Ferdian Thung, Shaowei Wang, David Lo, Julia Lawall
Automatic Recommendation Of Api Methods From Feature Requests, Ferdian Thung, Shaowei Wang, David Lo, Julia Lawall
Research Collection School Of Computing and Information Systems
Developers often receive many feature requests. To implement these features, developers can leverage various methods from third party libraries. In this work, we propose an automated approach that takes as input a textual description of a feature request. It then recommends methods in library APIs that developers can use to implement the feature. Our recommendation approach learns from records of other changes made to software systems, and compares the textual description of the requested feature with the textual descriptions of various API methods. We have evaluated our approach on more than 500 feature requests of Axis2/Java, CXF, Hadoop Common, HBase, …
Mining Branching-Time Scenarios, Dirk Fahland, David Lo, Shahar Maoz
Mining Branching-Time Scenarios, Dirk Fahland, David Lo, Shahar Maoz
Research Collection School Of Computing and Information Systems
Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows …
Got Issues? Who Cares About It? A Large Scale Investigation Of Issue Trackers From Github, Tegawende F. Bissyande, David Lo, Lingxiao Jiang, Laurent Reveillere, Jacques Klein, Yves Le Traon
Got Issues? Who Cares About It? A Large Scale Investigation Of Issue Trackers From Github, Tegawende F. Bissyande, David Lo, Lingxiao Jiang, Laurent Reveillere, Jacques Klein, Yves Le Traon
Research Collection School Of Computing and Information Systems
Feedback from software users constitutes a vital part in the evolution of software projects. By filing issue reports, users help identify and fix bugs, document software code, and enhance the software via feature requests. Many studies have explored issue reports, proposed approaches to enable the submission of higher-quality reports, and presented techniques to sort, categorize and leverage issues for software engineering needs. Who, however, cares about filing issues? What kind of issues are reported in issue trackers? What kind of correlation exist between issue reporting and the success of software projects? In this study, we address the need for answering …
Challenges And Opportunities In Taxi Fleet Anomaly Detection, Rijurekha Sen, Rajesh Krishna Balan
Challenges And Opportunities In Taxi Fleet Anomaly Detection, Rijurekha Sen, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
To enhance fleet operation and management, logistics companies instrument their vehicles with GPS receivers and network connectivity to servers. Mobility traces from such large fleets provide significant information on commuter travel patterns, traffic congestion and road anomalies, and hence several researchers have mined such datasets to gain useful urban insights. These logistics companies, however, incur significant cost in deploying and maintaining their vast network of instrumented vehicles. Thus research problems, that are not only of interest to urban planners, but to the logistics companies themselves are important to attract and engage these companies for collaborative data analysis. In this paper, …
From Rssi To Csi: Indoor Localization Via Channel Response, Zheng Yang, Zimu Zhou, Yunhao Liu
From Rssi To Csi: Indoor Localization Via Channel Response, Zheng Yang, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
The spatial features of emitted wireless signals are the basis of location distinction and determination for wireless indoor localization. Available in mainstream wireless signal measurements, the Received Signal Strength Indicator (RSSI) has been adopted in vast indoor localization systems. However, it suffers from dramatic performance degradation in complex situations due to multipath fading and temporal dynamics.
Tzuyu: Learning Stateful Typestates, Hao Xiao, Jun Sun, Yang Liu, Shang-Wei Lin, Chengnian Sun
Tzuyu: Learning Stateful Typestates, Hao Xiao, Jun Sun, Yang Liu, Shang-Wei Lin, Chengnian Sun
Research Collection School Of Computing and Information Systems
Behavioral models are useful for various software engineering tasks. They are, however, often missing in practice. Thus, specification mining was proposed to tackle this problem. Existing work either focuses on learning simple behavioral models such as finite-state automata, or relies on techniques (e.g., symbolic execution) to infer finite-state machines equipped with data states, referred to as stateful typestates. The former is often inadequate as finite-state automata lack expressiveness in capturing behaviors of data-rich programs, whereas the latter is often not scalable. In this work, we propose a fully automated approach to learn stateful typestates by extending the classic active learning …
A Scalable Approach For Malware Detection Through Bounded Feature Space Behavior Modeling, Mahinthan Chandramohan, Hee Beng Kuan Tan, Lionel C Briand, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
A Scalable Approach For Malware Detection Through Bounded Feature Space Behavior Modeling, Mahinthan Chandramohan, Hee Beng Kuan Tan, Lionel C Briand, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
Research Collection School Of Computing and Information Systems
In recent years, malware (malicious software) has greatly evolved and has become very sophisticated. The evolution of malware makes it difficult to detect using traditional signature-based malware detectors. Thus, researchers have proposed various behavior-based malware detection techniques to mitigate this problem. However, there are still serious shortcomings, related to scalability and computational complexity, in existing malware behavior modeling techniques. This raises questions about the practical applicability of these techniques. This paper proposes and evaluates a bounded feature space behavior modeling (BOFM) framework for scalable malware detection. BOFM models the interactions between software (which can be malware or benign) and security-critical …
Social-Loc: Improving Indoor Localization With Social Sensing, Jung-Hyun Jun, Yu Gu, Long Cheng, Banghui Lu, Jun Sun, Ting Zhu, Jianwei Niu
Social-Loc: Improving Indoor Localization With Social Sensing, Jung-Hyun Jun, Yu Gu, Long Cheng, Banghui Lu, Jun Sun, Ting Zhu, Jianwei Niu
Research Collection School Of Computing and Information Systems
Location-based services, such as targeted advertisement, geo-social networking and emergency services, are becoming increasingly popular for mobile applications. While GPS provides accurate outdoor locations, accurate indoor localization schemes still require either additional infrastructure support (e.g., ranging devices) or extensive training before system deployment (e.g., WiFi signal fingerprinting). In order to help existing localization systems to overcome their limitations or to further improve their accuracy, we propose Social-Loc, a middleware that takes the potential locations for individual users, which is estimated by any underlying indoor localization system as input and exploits both social encounter and non-encounter events to cooperatively calibrate the …
Understanding The Genetic Makeup Of Linux Device Drivers, Peter Senna Tschudin, Laurent Reveillere, Lingxiao Jiang, David Lo, Julia Lawall
Understanding The Genetic Makeup Of Linux Device Drivers, Peter Senna Tschudin, Laurent Reveillere, Lingxiao Jiang, David Lo, Julia Lawall
Research Collection School Of Computing and Information Systems
Attempts have been made to understand driver development in terms of code clones. In this paper, we propose an alternate view, based on the metaphor of a gene. Guided by this metaphor, we study the structure of Linux 3.10 ethernet platform driver probe functions.
Constraint-Based Automatic Symmetry Detection, Shao Jie Zhang, Jun Sun, Chengnian Sun, Yang Liu, Junwei Ma, Jin Song Dong
Constraint-Based Automatic Symmetry Detection, Shao Jie Zhang, Jun Sun, Chengnian Sun, Yang Liu, Junwei Ma, Jin Song Dong
Research Collection School Of Computing and Information Systems
We present an automatic approach to detecting symmetry relations for general concurrent models. Despite the success of symmetry reduction in mitigating state explosion problem, one essential step towards its soundness and effectiveness, i.e., how to discover sufficient symmetries with least human efforts, is often either overlooked or oversimplified. In this work, we show how a concurrent model can be viewed as a constraint satisfaction problem (CSP), and present an algorithm capable of detecting symmetries arising from the CSP which induce automorphisms of the model. To the best of our knowledge, our method is the first approach that can automatically detect …
Automatically Partition Software Into Least Privilege Components Using Dynamic Data Dependency Analysis, Yongzheng Wu, Jun Sun, Yang Liu, Jin Song Dong
Automatically Partition Software Into Least Privilege Components Using Dynamic Data Dependency Analysis, Yongzheng Wu, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
The principle of least privilege requires that software components should be granted only necessary privileges, so that compromising one component does not lead to compromising others. However, writing privilege separated software is difficult and as a result, a large number of software is monolithic, i.e., it runs as a whole without separation. Manually rewriting monolithic software into privilege separated software requires significant effort and can be error prone. We propose ProgramCutter, a novel approach to automatically partitioning monolithic software using dynamic data dependency analysis. ProgramCutter works by constructing a data dependency graph whose nodes are functions and edges are data …
Clustering Algorithms For Maximizing The Lifetime Of Wireless Sensor Networks With Energy-Harvesting Sensors, Pengfei Zhang, Gaoxi Xiao, Hwee-Pink Tan
Clustering Algorithms For Maximizing The Lifetime Of Wireless Sensor Networks With Energy-Harvesting Sensors, Pengfei Zhang, Gaoxi Xiao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Motivated by recent developments in wireless sensor networks (WSNs), we present several efficient clustering algorithms for maximizing the lifetime of WSNs, i.e., the duration till a certain percentage of the nodes die. Specifically, an optimization algorithm is proposed for maximizing the lifetime of a single-cluster network, followed by an extension to handle multi-cluster networks. Then we study the joint problem of prolonging network lifetime by introducing energy-harvesting (EH) nodes. An algorithm is proposed for maximizing the network lifetime where EH nodes serve as dedicated relay nodes for cluster heads (CHs). Theoretical analysis and extensive simulation results show that the proposed …
Todmis: Mining Communities From Trajectories, Siyuan Liu, Shuhui Wang, Kasthuri Jayarajah, Archan Misra, Rammaya Krishnan
Todmis: Mining Communities From Trajectories, Siyuan Liu, Shuhui Wang, Kasthuri Jayarajah, Archan Misra, Rammaya Krishnan
Research Collection School Of Computing and Information Systems
Existing algorithms for trajectory-based clustering usually rely on simplex representation and a single proximity-related distance (or similarity) measure. Consequently, additional information markers (e.g., social interactions or the semantics of the spatial layout) are usually ignored, leading to the inability to fully discover the communities in the trajectory database. This is especially true for human-generated trajectories, where additional fine-grained markers (e.g., movement velocity at certain locations, or the sequence of semantic spaces visited) can help capture latent relationships between cluster members. To address this limitation, we propose TODMIS: a general framework for Trajectory cOmmunity Discovery using Multiple Information Sources. TODMIS combines …
Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang
Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
What is the root cause of this failure? This question is often among the first few asked by software debuggers when they try to address issues raised by a bug report. Root cause is the erroneous lines of code that cause a chain of erroneous program states eventually leading to the failure. Bug tracking and source control systems only record the symptoms (e.g., bug reports) and treatments of a bug (e.g., committed changes that fix the bug), but not its root cause. Many treatments contain non-essential changes, which are intermingled with root causes. Reverse engineering the root cause of a …
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
Research Collection School Of Computing and Information Systems
Many third party libraries are available to be downloaded and used. Using such libraries can reduce development time and make the developed software more reliable. However, developers are often unaware of suitable libraries to be used for their projects and thus they miss out on these benefits. To help developers better take advantage of the available libraries, we propose a new technique that automatically recommends libraries to developers. Our technique takes as input the set of libraries that an application currently uses, and recommends other libraries that are likely to be relevant. We follow a hybrid approach that combines association …
Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang
Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
Accurate Developer Recommendation For Bug Resolution, Xin Xia, David Lo, Xinyu Wang, Bo Zhou
Accurate Developer Recommendation For Bug Resolution, Xin Xia, David Lo, Xinyu Wang, Bo Zhou
Research Collection School Of Computing and Information Systems
Bug resolution refers to the activity that developers perform to diagnose, fix, test, and document bugs during software development and maintenance. It is a collaborative activity among developers who contribute their knowledge, ideas, and expertise to resolve bugs. Given a bug report, we would like to recommend the set of bug resolvers that could potentially contribute their knowledge to fix it. We refer to this problem as developer recommendation for bug resolution. In this paper, we propose a new and accurate method named DevRec for the developer recommendation problem. DevRec is a composite method which performs two kinds of analysis: …
Creating Adaptive Quests To Support Personalized Learning Experiences When Learning Software Languages, Chris Boesch, Sandra Boesch
Creating Adaptive Quests To Support Personalized Learning Experiences When Learning Software Languages, Chris Boesch, Sandra Boesch
Research Collection School Of Computing and Information Systems
Over the past three years the authors have been developing and refining an online practicing platform called SingPath, which enables users to practice writing code in various software languages. The most recent feature to be released is a Quest mode that encourages users by showing short video clips each time a user solves five problems. In addition, users are able to choose whether to play through these quests on easy, medium, or hard levels of difficulty. The ability for users to customize their game play enables them to modify the difficulty of the experience and ideally self-regulate how frustrating or …
Cell: A Compositional Verification Framework, Kun Ji, Yang Liu, Jun Sun, Jun Sun, Jin Song Dong, Truong Khanh Nguyen
Cell: A Compositional Verification Framework, Kun Ji, Yang Liu, Jun Sun, Jun Sun, Jin Song Dong, Truong Khanh Nguyen
Research Collection School Of Computing and Information Systems
This paper presents CELL, a comprehensive and extensible framework for compositional verification of concurrent and real-time systems based on commonly used semantic models. For each semantic model, CELL offers three libraries, i.e., compositional verification paradigms, learning algorithms and model checking methods to support various state-of-the-art compositional verification approaches. With well-defined APIs, the framework could be applied to build customized model checkers. In addition, each library could be used independently for verification and program analysis purposes. We have built three model checkers with CELL. The experimental results show that the performance of these model checkers can offer similar or often better …
Skyhunter: A Multi-Surface Environment For Supporting Oil And Gas Exploration, Teddy Seyed, Mario Costa Sousa, Frank Maurer, Anthony Tang
Skyhunter: A Multi-Surface Environment For Supporting Oil And Gas Exploration, Teddy Seyed, Mario Costa Sousa, Frank Maurer, Anthony Tang
Research Collection School Of Computing and Information Systems
The process of oil and gas exploration and its result, the decision to drill for oil in a specific location, relies on a number of distinct but related domains. These domains require effective collaboration to come to a decision that is both cost effective and maintains the integrity of the environment. As we show in this paper, many of the existing technologies and practices that support the oil and gas exploration process overlook fundamental user issues such as collaboration, interaction and visualization. The work presented in this paper is based upon a design process that involved expert users from an …
Livelabs: Initial Reflections On Building A Large-Scale Mobile Behavioral Experimentation Testbed, Archan Misra, Rajesh Krishna Balan
Livelabs: Initial Reflections On Building A Large-Scale Mobile Behavioral Experimentation Testbed, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
We believe that, for successful adoption of novel mobile technologies and applications, it is important to be able to test them under real usage patterns, and with real users. To implement this vision, we present our initial effort in building LiveLabs, a large-scale mobile testbed for in-situ experimentation. LiveLabs is unique in two aspects. First, LiveLabs operates on a scale much larger than most research testbeds— it is being deployed in four different public spaces in Singapore (a university campus, a shopping mall, an airport and a leisure resort), and is expected to have a pool of over 30,000 opt-in …
An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li
An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li
Research Collection School Of Computing and Information Systems
Inter-user interference degrades the reliability of data delivery in wireless body sensor networks (WBSNs) in dense deployments when multiple users wearing WBSNs are in close proximity to one another. The impact of such interference in realistic WBSN systems is significant but is not well explored. To this end, we investigate and analyze the impact of inter-user interference on packet delivery ratio (PDR) and throughput. We conduct extensive experiments based on the TelosB WBSN platform, considering unslotted carrier sense multiple access (CSMA) with collision avoidance (CA) and slotted CSMA/CA modes in IEEE 802.15.4 MAC, respectively. In order to mitigate interuser interference, …
Adaptive Gameplay For Programming Practice, Chris Boesch, Sandra Boesch
Adaptive Gameplay For Programming Practice, Chris Boesch, Sandra Boesch
Research Collection School Of Computing and Information Systems
Over the past four years, we have collaborated to develop a set of online games to enable users to practice software languages in a self-directed manner and as part of a class. Recently we introduced a new adaptive difficulty feature that enables players to self-regulate the difficulty of the games they are playing to practice. These new features also provide additional information to further adapt the problem content to better meet the needs of the users.
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Despite the important role that WiFi networks play in home and enterprise networks they are relatively weak from a security standpoint. With easily available directional antennas, attackers can be physically located off-site, yet compromise WiFi security protocols such as WEP, WPA, and even to some extent WPA2 through a range of exploits specific to those protocols, or simply by running dictionary and human-factors attacks on users' poorly-chosen passwords. This presents a security risk to the entire home or enterprise network. To mitigate this ongoing problem, we propose SecureArray, a system designed to operate alongside existing wireless security protocols, adding defense …
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we present the design and implementation of Focus, a system for effectively and efficiently reducing power consumption of OLED displays on smartphones. These displays, while becoming exceedingly common still consume significant power. The key idea of Focus is that we use the notion of saliency to save display power by dimming portions of the applications that are less important to the user. We envision Focus being especially useful during low battery situations when usability is less important than power savings. We tested Focus using 15 applications running on a Samsung Galaxy S III and show that it …