Software Engineering Commons^™

Fine-Grained Appliance Usage And Energy Monitoring Through Mobile And Power-Line Sensing, Nirmalya Roy, Nilavra Pathak, Archan Misra

Research Collection School Of Computing and Information Systems

To promote energy-efficient operations in residential and office buildings, non-intrusive load monitoring (NILM) techniques have been proposed to infer the fine-grained power consumption and usage patterns of appliances from power-line measurement data. Fine-grained monitoring of everyday appliances (such as toasters and coffee makers) can not only promote energy-efficient building operations, but also provide unique insights into the context and activities of individuals. Current building-level NILM techniques are unable to identify the consumption characteristics of relatively low-load appliances, whereas smart-plug based solutions incur significant deployment and maintenance costs. In this paper, we investigate an intermediate architecture, where smart circuit breakers provide …

Comon+: A Cooperative Context Monitoring System For Multi-Device Personal Sensing Environments, Youngki Lee, Seungwoo Kang, Chulhong Min, Younghyun Ju, Inseok Hwang, Junehwa Song

Research Collection School Of Computing and Information Systems

Continuous mobile sensing applications are emerging. Despite their usefulness, their real-world adoption has been slow. Many users are turned away by the drastic battery drain caused by continuous sensing and processing. In this paper, we propose CoMon+, a novel cooperative context monitoring system, which addresses the energy problem through opportunistic cooperation among nearby users. For effective cooperation, we develop a benefit-aware negotiation method to maximize the energy benefit of context sharing. CoMon+ employs heuristics to detect cooperators who are likely to remain in the vicinity for a long period of time, and the negotiation method automatically devises a cooperation plan …

Ciliate Codon Translator Program Manual, Quentin D. Altemose

Mathematics Summer Fellows

Understanding the evolutionary history of organisms allows us to better comprehend selective pressures and their effects on larger populations. In our study, we focused on analyzing the DNA of ciliate groups, which are single celled protozoans characterized by the presence of cilia on their outer membrane. We utilized the DNA of the organisms to analyze the changes in population genotype over time. We tested existing evolutionary models (designed to represent natural genetic variation over time in populations) against our data to identify the model with the best fit and likelihood. From the DNA and the evolutionary model with the highest …

On Understanding Preference For Agile Methods Among Software Developers, David Brian Bishop, Amit V. Deokar, Surendra Sarnikar

Research & Publications

Agile methods are gaining widespread use in industry. Although management is keen on adopting agile, not all developers exhibit preference for agile methods. The literature is sparse in regard to why developers may show preference for agile. Understanding the factors informing the preference for agile can lead to more effective formation of teams, better training approaches, and optimizing software development efforts by focusing on key desirable components of agile. This study, using a grounded theory methodology, finds a variety of categories of factors that influence software developer preference for agile methods including self-efficacy, affective response, interpersonal response, external contingencies, and …

Mhealth Support System For Researchers And Participants, Taskina Fayezeen

Master's Theses (2009 -)

With the proliferation of mobile technologies, there is a significant increase of research using mobile devices in the medical and public health area. Mobile technology has improved the efficiency of healthcare delivery effectively. Mobile Health or mHealth is an interdisciplinary research area which has been active for more than a decade. Much research has been conducted and many software research tools (mHealth Support System) have been developed. Despite the time length, there is a significant gap in the mHealth research area regarding software research tools. Individual research groups are developing their own software research tool though there is a significant …

A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske

Research Collection School Of Computing and Information Systems

Debugging is a costly process that consumes much of developer time and energy. To help reduce debugging effort, many studies have proposed various fault localization approaches. These approaches take as input a set of test cases (some failing, some passing) and produce a ranked list of program elements that are likely to be the root cause of the failures (i.e., failing test cases). In this work, we propose Savant, a new fault localization approach that employs a learning-to-rank strategy, using likely invariant diffs and suspiciousness scores as features, to rank methods based on their likelihood to be a root cause …

Satisfiability Modulo Heap-Based Programs, Quang Loc Le, Jun Sun, Wei-Ngan Chin

Research Collection School Of Computing and Information Systems

In this work, we present a semi-decision procedure for a fragment of separation logic with user-defined predicates and Presburger arithmetic. To check the satisfiability of a formula, our procedure iteratively unfolds the formula and examines the derived disjuncts. In each iteration, it searches for a proof of either satisfiability or unsatisfiability. Our procedure is further enhanced with automatically inferred invariants as well as detection of cyclic proof. We also identify a syntactically restricted fragment of the logic for which our procedure is terminating and thus complete. This decidable fragment is relatively expressive as it can capture a range of sophisticated …

Proxy Signature With Revocation, Shengmin Xu, Guomin Yang, Yi Mu, Shu Ma

Research Collection School Of Computing and Information Systems

Proxy signature is a useful cryptographic primitive that allows signing right delegation. In a proxy signature scheme, an original signer can delegate his/her signing right to a proxy signer (or a group of proxy signers) who can then sign documents on behalf of the original signer. In this paper, we investigate the problem of proxy signature with revocation. The revocation of delegated signing right is necessary for a proxy signature scheme when the proxy signer’s key is compromised and/or any misuse of the delegated right is noticed. Although a proxy signature scheme usually specifies a delegation time period, it may …

Passively Testing Routing Protocols In Wireless Sensor Networks, Xiaoping Che, Stephane Maag, Hwee-Xian Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Smart systems are today increasingly developed with the number of wireless sensor devices that drastically increases. They are implemented within several contexts through our environment. Thus, sensed data transported in ubiquitous systems are important and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed to wireless sensor networks (WSN). However, one stage that is often neglected before their deployment, is the conformance testing process, a crucial and challenging step. Active testing techniques commonly used in wired networks are not suitable to WSN and passive approaches are needed. While some works …

Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu

Research Collection School Of Computing and Information Systems

Cross-modal hashing integrates the advantages of traditional cross-modal retrieval and hashing, it can solve large-scale cross-modal retrieval effectively and efficiently. However, existing cross-modal hashing methods rely on either labeled training data, or lack semantic analysis. In this paper, we propose Cross-Modal Self-Taught Hashing (CMSTH) for large-scale cross-modal and unimodal image retrieval. CMSTH can effectively capture the semantic correlation from unlabeled training data. Its learning process contains three steps: first we propose Hierarchical Multi-Modal Topic Learning (HMMTL) to detect multi-modal topics with semantic information. Then we use Robust Matrix Factorization (RMF) to transfer the multi-modal topics to hash codes which are …

Lack Of Attention To Singular (Or Atomic) Requirements Despite Benefits For Quality, Metrics And Management, William L. Honig, Shingo Takada, Natsuko Noda

Computer Science: Faculty Publications and Other Works

There are seemingly many advantages to being able to identify, document, test, and trace single or “atomic” requirements. Why then has there been little attention to the topic and no widely used definition or process on how to define atomic requirements?

Definitions of requirements and standards focus on user needs, system capabilities or functions; some definitions include making individual requirements singular or without the use of conjunctions. In a few cases there has been a description of atomic system events or requirements. This work is surveyed here although there is no well accepted and used best practice for generating atomic …

Stpp: Spatial-Temporal Phase Profiling Based Method For Relative Rfid Tag Localization, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu

Research Collection School Of Computing and Information Systems

Many object localization applications need the relative locations of a set of objects as oppose to their absolute locations. Although many schemes for object localization using radio frequency identification (RFID) tags have been proposed, they mostly focus on absolute object localization and are not suitable for relative object localization because of large error margins and the special hardware that they require. In this paper, we propose an approach called spatial-temporal phase profiling (STPP) to RFID-based relative object localization. The basic idea of STPP is that by moving a reader over a set of tags during which the reader continuously interrogating …

Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Software engineering practitioners often spend significant amount of time and effort to debug. To help practitioners perform this crucial task, hundreds of papers have proposed various fault localization techniques. Fault localization helps practitioners to find the location of a defect given its symptoms (e.g., program failures). These localization techniques have pinpointed the locations of bugs of various systems of diverse sizes, with varying degrees of success, and for various usage scenarios. Unfortunately, it is unclear whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by surveying 386 practitioners from more than 30 countries …

Metrics, Software Engineering, Small Systems – The Future Of Systems Development, William L. Honig

Computer Science: Faculty Publications and Other Works

In this talk I will introduce the importance of metrics, or measures, and the role they play in the development of high quality computer systems. I will review some key mega trends in computer science over the last three decades and then explain why I believe the trend to small networked systems, along with metrics and software engineering will define the future of high technology computer based systems.

I first learned about metrics at the Bell System where everything was measured. Metrics can be understood easily if you think of them as measures, for example of calories or salt in …

An Interference-Free Programming Model For Network Objects, Mischael Schill, Christopher M. Poskitt, Bertrand Meyer

Research Collection School Of Computing and Information Systems

Network objects are a simple and natural abstraction for distributed object-oriented programming. Languages that support network objects, however, often leave synchronization to the user, along with its associated pitfalls, such as data races and the possibility of failure. In this paper, we present D-Scoop, a distributed programming model that allows for interference-free and transaction-like reasoning on (potentially multiple) network objects, with synchronization handled automatically, and network failures managed by a compensation mechanism. We achieve this by leveraging the runtime semantics of a multi-threaded object-oriented concurrency model, directly generalizing it with a message-based protocol for efficiently coordinating remote objects. We present …

Why A Testing Career Is Not The First Choice Of Engineers, Pradeep Kashinath Waychal, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

No abstract provided.

Automating Self Evaluations For Software Engineers, Jonathan Rodrigo A. Miranda

Master's Theses

Software engineers frequently compose self-evaluations as part of employee perfor- mance reviews. These evaluations can be a key artifact for assessing a software engineer’s contributions to a team and organization, and for generating useful feed- back. Self-evaluations can be challenging because a) they can be time consuming, b) individuals may forget about important contributions especially when the review period is long such as a full year, c) some individuals can consciously or unconsciously overstate their contributions, and d) some individuals can be reluctant to describe their contributions for fear of appearing too proud [24].

UNBIASED, Useful New Basic Interactive Automated …

Deepsense: A Gpu-Based Deep Convolutional Neural Network Framework On Commodity Mobile Devices, Huynh Nguyen Loc, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Recently, a branch of machine learning algorithms called deep learning gained huge attention to boost up accuracy of a variety of sensing applications. However, execution of deep learning algorithm such as convolutional neural network on mobile processor is non-trivial due to intensive computational requirements. In this paper, we present our early design of DeepSense - a mobile GPU-based deep convolutional neural network (CNN) framework. For its design, we first explored the differences between server-class and mobile-class GPUs, and studied effectiveness of various optimization strategies such as branch divergence elimination and memory vectorization. Our results show that DeepSense is able to …

Fusing Wifi And Video Sensing For Accurate Group Detection In Indoor Spaces, Kasthuri Jayarajah, Zaman Lantra, Archan Misra

Research Collection School Of Computing and Information Systems

Understanding one's group context in indoor spaces is useful for many reasons - e.g., at a shopping mall, knowing a customer's group context can help in offering context-specific incentives, or estimating taxi demand for customers exiting the mall. Group detection and monitoring using WiFi-based indoor location traces fails when users are invisible (either because they don't carry smartphones, or because their WiFi is turned OFF) or when location tracking is inaccurate. In this paper, we propose a multi-modal group detection system that fuses two independent modes: video and WiFi, for detecting groups with low latency and high accuracy. We present …

How Long Will This Live? Discovering The Lifespans Of Software Engineering Ideas, Subhajit Datta, Santonu Sarkar, A. S. M Sajeev

Research Collection School Of Computing and Information Systems

We all want to be associated with long lasting ideas; as originators, or at least, expositors. For a tyro researcher or a seasoned veteran, knowing how long an idea will remain interesting in the community is critical in choosing and pursuing research threads. In the physical sciences, the notion of half-life is often evoked to quantify decaying intensity. In this paper, we study a corpus of 19,000+ papers written by 21,000+ authors across 16 software engineering publication venues from 1975 to 2010, to empirically determine the half-life of software engineering research topics. In the absence of any consistent and well-accepted …

Demo: Drumming Application Using Commodity Wearable Devices, Bharat Dwivedi, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

We aim to develop a drumming application in which individual can play drums using multiple wearable and mobile devices. Our vision is to tap out different rythms in the air using smart watches as a virtual drum stick and smart phone would act as a drum kit. Same user interface can be visualized in smart glasses. Here, our prime target is to use multiple commodity wearable devices (non-commodity i.e. Myo arm band) and smart phones for recognizing new (or same type of here) types of multi limb gestural context and building an adaptive application interface and allow such gesture recognition …

Demo: Gpu-Based Image Recognition And Object Detection On Commodity Mobile Devices, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

In this demo, we show that it is feasible to execute CNN for vision sensing tasks directly on mobile devices by leveraging integrated GPU. We propose our design of DeepSense framework based on OpenCL to execute deep learning algorithms in energy-efficient and fast manner.

Demo: Multi-Device Gestural Interfaces, Tran Huy Vu, Youngki Lee, Archan Misra

Research Collection School Of Computing and Information Systems

Varieties of wearable devices such as smart watches, Virtual/Augmented Reality devices (AR/VR) are much more affordable with interesting capabilities. In our vision, a person may use more than one devices at a time, and they form an eco-system of wearable devices. Therefore, we aim to build a system where an application expands its input and output among different devices, and adapts its input/output stream for different contexts.

Livelabs: Building In-Situ Mobile Sensing And Behavioural Experimentation Testbeds, Kasthuri Jayarajah, Rajesh Krishna Balan, Meera Radhakrishnan, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we present LiveLabs, a first-of-its-kind testbed that isdeployed across a university campus, convention centre, and resortisland and collects real-time attributes such as location, group contextetc., from hundreds of opt-in participants. These venues, data,and participants are then made available for running rich humancentricbehavioural experiments that could test new mobile sensinginfrastructure, applications, analytics, or more social-sciencetype hypotheses that influence and then observe actual user behaviour.We share case studies of how researchers from aroundthe world have and are using LiveLabs, and our experiences andlessons learned from building, maintaining, and expanding LiveLabsover the last three years.

Jasper: Sensing Gamers' Emotions Using Physiological Sensors, Sinh Huynh, Youngki Lee, Taiwoo Park, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper aims to develop a system that evaluates the emotional experience of gamers based on physiological changes. A within-subject experiment with 22 participants has been designed to investigate the effects of difficulty level and social playing mode on player emotions and to examine the correlation between each emotion and the physiological changes. We demonstrate the feasibility of using commodity wearable physiological sensing devices to recognize mobile gamer's emotion. Specifically, our system performs 3-level excitement classification at an accuracy of 77.38% and binary classification of happiness state at an accuracy of 73.21%. These classification results show the potential of using …

Small Scale Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang Huy, Gihan Hettiarachchi, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In this paper, we present the results of a small-scale field deployment of our capacitance-based seat occupancy detector. We deployed our sensors to 36 seats in our university library and measured the performance of our system over a period of 8 weeks. As part of this deployment, we had to tackle numerous real-world deployment issues such as hardware failure, variations in signal quality, and interference caused by multiple objects in near proximity. We present our overall system design, along with the modifications we made to tackle various real-world problems. Finally, we present the results of our deployment which showed that …

Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang

Research Collection School Of Computing and Information Systems

No abstract provided.

Efficient Multi-Class Selective Sampling On Graphs, Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Hoi, Steven C. H., Xiao-Li Li

Research Collection School Of Computing and Information Systems

A graph-based multi-class classification problem is typically converted into a collection of binary classification tasks via the one-vs.-all strategy, and then tackled by applying proper binary classification algorithms. Unlike the one-vs.-all strategy, we suggest a unified framework which operates directly on the multi-class problem without reducing it to a collection of binary tasks. Moreover, this framework makes active learning practically feasible for multi-class problems, while the one-vs.-all strategy cannot. Specifically, we employ a novel randomized query technique to prioritize the informative instances. This query technique based on the hybrid criterion of "margin" and "uncertainty" can achieve a comparable mistake bound …

Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia Zakaria, Richard C. Davis

Research Collection School Of Computing and Information Systems

Managing problem behaviors in children with neurodevelopmental disorders can be challenging. Such behaviors may discourage social participation and learning. Many of these behaviors warrant intervention, however, are challenging for caregivers to constantly supervise. Previous work focused on developing recognition systems for stereotypical and aggressive behaviors. Researchers also developed visualization interface for caregivers to better understand their child’s needs. Our goal however, is to design an independent behavior management application to help children manage problem behaviors with minimal supervision.We conducted a field study at a school for children with special needs in Singapore, and interviewed ten teachers. This study helped us …

Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra

Research Collection School Of Computing and Information Systems

We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.