Computer Sciences Commons^™

Open Source Foundations For Spatial Decision Support Systems, Jochen Albrecht

Publications and Research

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools …

Multi-Task Zipping Via Layer-Wise Neuron Sharing, Xiaoxi He, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks on-device. Yet the complexity of these neural networks needs to be trimmed down both within-model and cross-model to fit in mobile storage and memory. Previous studies squeeze the redundancy within a single model. In this work, we aim to reduce the redundancy across multiple models. We propose Multi-Task Zipping (MTZ), a framework to automatically merge correlated, pre-trained deep neural networks for cross-model compression. Central in MTZ is a layer-wise neuron sharing and incoming weight updating scheme that …

Comparison Mining From Text, Maksim Tkachenko

Dissertations and Theses Collection (Open Access)

Online product reviews are important factors of consumers' purchase decisions. They invade more and more spheres of our life, we have reviews on books, electronics, groceries, entertainments, restaurants, travel experiences, etc. More than 90 percent of consumers read online reviews before they purchase products as reported by various consumers surveys. This observation suggests that product review information enhances consumer experience and helps them to make better-informed purchase decisions. There is an enormous amount of online reviews posted on e-commerce platforms, such as Amazon, Apple, Yelp, TripAdvisor. They vary in information and may be written with different experiences and preferences.

If …

Eye Pressure Monitior, Andrea Nella Levy

Computer Engineering

The document describes a mobile application that takes information from an attached device which tests eye pressure. The device consists of an IOIO board connected to a custom device that measures the frequency of a given waveform. The device was designed by another student for their senior project, which I am taking over. This device is connected to an IOIO board which is a board designed by a Google employee which works with an android phone in order to create applications that work with embedded systems. The board comes with an API and connects to the phone via a micro-USB. …

Effectiveness Of Physical Robot Versus Robot Simulator In Teaching Introductory Programming, Oka Kurniawan, Norman Tiong Seng Lee, Subhajit Datta, Nachamma Sockalingam, Pey Lin Leong

Research Collection School Of Computing and Information Systems

This study reports the use of a physical robot and robot simulator in an introductory programming course in a university and measures students' programming background conceptual learning gain and learning experience. One group used physical robots in their lessons to complete programming assignments, while the other group used robot simulators. We are interested in finding out if there is any difference in the learning gain and experiences between those that use physical robots as compared to robot simulators. Our results suggest that there is no significant difference in terms of students' learning between the two approaches. However, the control group …

Message From The Chairs, Toshiki Hirao, Yutaro Kashiwa, Christoph Treude, Raula Gaikovina Kula

Research Collection School Of Computing and Information Systems

It is our great pleasure to welcome everyone to the 2018 International Workshop on Empirical Software Engineering in Practice (IWESEP 2018). Our workshop aims to foster the development of the area by providing a forum where researchers and practitioners can report on and discuss new research results and applications in the area of empirical software engineering. The workshop encourages the exchange of ideas within the international community so as to be able to understand, from an empirical viewpoint, the strengths and weaknesses of technology in use and new technologies, with the expectation of advancing the field of software engineering in …

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show that …

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of …

Perflearner: Learning From Bug Reports To Understand And Generate Performance Test Frames, Xue Han, Tingting Yu, David Lo

Research Collection School Of Computing and Information Systems

Software performance is important for ensuring the quality of software products. Performance bugs, defined as programming errors that cause significant performance degradation, can lead to slow systems and poor user experience. While there has been some research on automated performance testing such as test case generation, the main idea is to select workload values to increase the program execution times. These techniques often assume the initial test cases have the right combination of input parameters and focus on evolving values of certain input parameters. However, such an assumption may not hold for highly configurable real-word applications, in which the combinations …

Applying Design Thinking To Student Outreach Projects: Experiences From An Information Systems School, Swapna Gottipati, Venky Shankararaman, Alan Megargel

Research Collection School Of Computing and Information Systems

As countries turn into Smart Nations, Infocom Technology plays a key role in enhancing their competitiveness through high skilled workforces. Reaching to younger generations and attracting them to computing programs such as Information Systems (IS) and Computer Science (CS) is a key challenge faced by universities. Many high quality students from junior colleges either don’t choose IS programs or choose IS programs as their last option during the application process. A School of Information Systems (SIS) from a large metropolitan university decided to implement an innovative outreach program to attract high quality high school aka Junior College (JC) students. JC …

Privacy-Preserving Remote User Authentication With K-Times Untraceability, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Robert H. Deng, Albert Ching, Weiwei Liu

Research Collection School Of Computing and Information Systems

Remote user authentication has found numerous real-world applications, especially in a user-server model. In this work, we introduce the notion of anonymous remote user authentication with k-times untraceability (k-RUA) for a given parameter k, where authorized users authenticate themselves to an authority (typically a server) in an anonymous and k-times untraceable manner. We define the formal security models for a generic k-RUA construction that guarantees user authenticity, anonymity and user privacy. We provide a concrete instantiation of k-RUA having the following properties: (1) a third party cannot impersonate an authorized user by producing valid transcripts for the user while conversing …

Automatically `Verifying’ Discrete-Time Complex Systems Through Learning, Abstraction And Refinement, Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jegourel

Research Collection School Of Computing and Information Systems

Precisely modeling complex systems like cyber-physical systems is challenging, which often render model-based system verification techniques like model checking infeasible. To overcome this challenge, we propose a method called LAR to automatically ‘verify’ such complex systems through a combination of learning, abstraction and refinement from a set of system log traces. We assume that log traces and sampling frequency are adequate to capture ‘enough’ behaviour of the system. Given a safety property and the concrete system log traces as input, LAR automatically learns and refines system models, and produces two kinds of outputs. One is a counterexample with a bounded …

Co-Location Resistant Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Due to increasing number of avenues for conducting cross-virtual machine (VM) side-channel attacks, the security of public IaaS cloud data centers is a growing concern. These attacks allow an adversary to steal private information from a target user whose VM instance is co-located with that of the adversary. To reduce the probability of malicious co-location, we propose a novel VM placement algorithm called “Previously Co-Located Users First”. We perform a theoretical and empirical analysis of our proposed algorithm to evaluate its resource efficiency and security. Our results, obtained using real-world cloud traces containing millions of VM requests and thousands of …

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …

Phr: Patient Health Record, Quinn Nelson

Theses/Capstones/Creative Projects

The rapid development of information technology systems has expanded into multiple disciplines and results in systems that are limited by initial design and implementation: the Healthcare Information Technology (HIT) space is no different. The introduction of the Electronic Health Record (EHR) system has changed the way healthcare operates. Initial designs of these systems were focused on serving the needs of insurance companies and healthcare billing departments. Research shows that the design of EHR systems negatively impact provider-patient interactions and the care they receive. This capstone project capitalizes on the collaboration efforts between UNO and UNMC – by joining a research …

Social Software Development: Insights And Solutions, Abhishek Sharma

Dissertations and Theses Collection (Open Access)

Over last few decades, the way software is developed has changed drastically. From being an activity performed by developers working individually to develop standalone programs, it has transformed into a highly collaborative and cooperative activity. Software development today can be considered as a participatory culture, where developers coordinate and engage together to develop software while continuously learning from one another and creating knowledge.

In order to support their communication and collaboration needs, software developers often use a variety of social media channels. These channels help software developers to connect with like-minded developers and explore collaborations on software projects of interest. …

Adaptive Parallelism For Coupled, Multithreaded Message-Passing Programs, Samuel K. Gutiérrez

Computer Science ETDs

Hybrid parallel programming models that combine message passing (MP) and shared- memory multithreading (MT) are becoming more popular, especially with applications requiring higher degrees of parallelism and scalability. Consequently, coupled parallel programs, those built via the integration of independently developed and optimized software libraries linked into a single application, increasingly comprise message-passing libraries with differing preferred degrees of threading, resulting in thread-level heterogeneity. Retroactively matching threading levels between independently developed and maintained libraries is difficult, and the challenge is exacerbated because contemporary middleware services provide only static scheduling policies over entire program executions, necessitating suboptimal, over-subscribed or under-subscribed, configurations. In …

Cleaver: Classification Of Everyday Activities Via Ensemble Recognizers, Samantha Hsu

Master's Theses

Physical activity can have immediate and long-term benefits on health and reduce the risk for chronic diseases. Valid measures of physical activity are needed in order to improve our understanding of the exact relationship between physical activity and health. Activity monitors have become a standard for measuring physical activity; accelerometers in particular are widely used in research and consumer products because they are objective, inexpensive, and practical. Previous studies have experimented with different monitor placements and classification methods. However, the majority of these methods were developed using data collected in controlled, laboratory-based settings, which is not reliably representative of real …

Criticality Assessments For Improving Algorithmic Robustness, Thomas B. Jones

Computer Science ETDs

Though computational models typically assume all program steps execute flawlessly, that does not imply all steps are equally important if a failure should occur. In the "Constrained Reliability Allocation" problem, sufficient resources are guaranteed for operations that prompt eventual program termination on failure, but those operations that only cause output errors are given a limited budget of some vital resource, insufficient to ensure correct operation for each of them.

In this dissertation, I present a novel representation of failures based on a combination of their timing and location combined with criticality assessments---a method used to predict the behavior of systems …

Delta Debugging Microservice Systems, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Wenhai Li, Chao Ji, Dan Ding

Research Collection School Of Computing and Information Systems

Debugging microservice systems involves the deployment and manipulation of microservice systems on a containerized environment and faces unique challenges due to the high complexity and dynamism of microservices. To address these challenges, in this paper, we propose a debugging approach for microservice systems based on the delta debugging algorithm, which is to minimize failureinducing deltas of circumstances (e.g., deployment, environmental configurations) for effective debugging. Our approach includes novel techniques for defining, deploying/manipulating, and executing deltas following the idea of delta debugging. In particular, to construct a (failing) circumstance space for delta debugging to minimize, our approach defines a set of …

Learning Probabilistic Models For Model Checking: An Evolutionary Approach And An Empirical Study, Jingyi Wang, Jun Sun, Qixia Yuan, Jun Pang

Research Collection School Of Computing and Information Systems

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically “learn” models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on …

Learning Generalized Video Memory For Automatic Video Captioning, Poo-Hee Chang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Recent video captioning methods have made great progress by deep learning approaches with convolutional neural networks (CNN) and recurrent neural networks (RNN). While there are techniques that use memory networks for sentence decoding, few work has leveraged on the memory component to learn and generalize the temporal structure in video. In this paper, we propose a new method, namely Generalized Video Memory (GVM), utilizing a memory model for enhancing video description generation. Based on a class of self-organizing neural networks, GVM’s model is able to learn new video features incrementally. The learned generalized memory is further exploited to decode the …

Aligning Technical Debt Prioritization With Business Objectives: A Multiple-Case Study, Rodrigo Rebouças De Almeida, Uirá Kulesza, Christoph Treude, D’Angellys Cavalcanti Feitosa, Aliandro Higino Guedes Lima

Research Collection School Of Computing and Information Systems

Technical debt (TD) is a metaphor to describe the trade-off between short-term workarounds and long-term goals in software development. Despite being widely used to explain technical issues in business terms, industry and academia still lack a proper way to manage technical debt while explicitly considering business priorities. In this paper, we report on a multiple-case study of how two big software development companies handle technical debt items, and we show how taking the business perspective into account can improve the decision making for the prioritization of technical debt. We also propose a first step toward an approach that uses business …

Artefact: An R Implementation Of The Autospearman Function, Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude

Research Collection School Of Computing and Information Systems

This artefact is the implementation of AutoSpearman, an automated metric selection approach based on correlation analyses. The goal of AutoSpearman is to automatically mitigate correlated metrics prior to constructing analytical models. This artefact is implemented as an R package and is available in the GitHub repository. We provide descriptions and R code snippets for the installation of AutoSpearman and usage examples.

Autospearman: Automatically Mitigating Correlated Software Metrics For Interpreting Defect Models, Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude

Research Collection School Of Computing and Information Systems

The interpretation of defect models heavily relies on software metrics that are used to construct them. However, such software metrics are often correlated in defect models. Prior work often uses feature selection techniques to remove correlated metrics in order to improve the performance of defect models. Yet, the interpretation of defect models may be misleading if feature selection techniques produce subsets of inconsistent and correlated metrics. In this paper, we investigate the consistency and correlation of the subsets of metrics that are produced by nine commonly-used feature selection techniques. Through a case study of 13 publicly-available defect datasets, we find …

Ten Years Of Hunting For Similar Code For Fun And Profit (Keynote), Stephane Glondu, Lingxiao Jiang, Zhendong Su

Research Collection School Of Computing and Information Systems

In 2007, the Deckard paper was published at ICSE. Since its publication, it has led to much follow-up research and applications. The paper made two core contributions: a novel vector embedding of structured code for fast similarity detection, and an application of the embedding for clone detection, resulting in the Deckard tool. The vector embedding is simple and easy to adapt. Similar code detection is also fundamental for a range of classical and emerging problems in software engineering, security, and computer science education (e.g., code reuse, refactoring, porting, translation, synthesis, program repair, malware detection, and feedback generation). Both have buttressed …

Vt-Revolution: Interactive Programming Tutorials Made Possible, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Programming video tutorials showcase programming tasks and associated workflows. Although video tutorials are easy to create, it isoften difficult to explore the captured workflows and interact withthe programs in the videos. In this work, we propose a tool named VTRevolution – an interactive programming video tutorial authoring system. VTRevolution has two components: 1) a tutorial authoring system leverages operating system level instrumentation to log workflow history while tutorial authors are creating programming video tutorials; 2) a tutorial watching system enhances the learning experience of video tutorials by providing operation history and timeline-based browsing interactions. Our tutorial authoring system does not …

Infar: Insight Extraction From App Reviews, Cuiyun Gao, Jichuan Zeng, David Lo, Chin-Yew Lin, Michael R. Lyu, Irwin King

Research Collection School Of Computing and Information Systems

App reviews play an essential role for users to convey their feedback about using the app. The critical information contained in app reviews can assist app developers for maintaining and updating mobile apps. However, the noisy nature and large-quantity of daily generated app reviews make it difficult to understand essential information carried in app reviews. Several prior studies have proposed methods that can automatically classify or cluster user reviews into a few app topics (e.g., security). These methods usually act on a static collection of user reviews. However, due to the dynamic nature of user feedback (i.e., reviews keep coming …

Dsm: A Specification Mining Tool Using Recurrent Neural Network Based Language Model, Tien-Duy B. Le, Lingfeng Bao, David Lo

Research Collection School Of Computing and Information Systems

Formal specifications are important but often unavailable. Furthermore, writing these specifications is time-consuming and requires skills from developers. In this work, we present Deep Specification Miner (DSM), an automated tool that applies deep learning to mine finite-state automaton (FSA) based specifications. DSM accepts as input a set of execution traces to train a Recurrent Neural Network Language Model (RNNLM). From the input traces, DSM creates a Prefix Tree Acceptor (PTA) and leverages the inferred RNNLM to extract many features. These features are then forwarded to clustering algorithms for merging similar automata states in the PTA for assembling a number of …

Using Finite-State Models For Log Differencing, Hen Amar, Lingfeng Bao, Nimrod Busany, David Lo, Shahar Maoz

Research Collection School Of Computing and Information Systems

Much work has been published on extracting various kinds of models from logs that document the execution of running systems. In many cases, however, for example in the context of evolution, testing, or malware analysis, engineers are interested not only in a single log but in a set of several logs, each of which originated from a different set of runs of the system at hand. Then, the difference between the logs is the main target of interest. In this work we investigate the use of finite-state models for log differencing. Rather than comparing the logs directly, we generate concise …