Software Engineering Commons^™

Diversity Maximization Speedup For Localizing Faults In Single-Fault And Multi-Fault Programs, Xin Xia, Liang Gong, Tien-Duy B. Le, David Lo, Lingxiao Jiang, Hongyu Zhang

Research Collection School Of Computing and Information Systems

Fault localization is useful for reducing debugging effort. Such techniques require test cases with oracles, which can determine whether a program behaves correctly for every test input. Although most fault localization techniques can localize faults relatively accurately even with a small number of test cases, choosing the right test cases and creating oracles for them are not easy. Test oracle creation is expensive because it can take much manual labeling effort (i.e., effort needed to decide whether the test cases pass or fail). Given a number of test cases to be executed, it is challenging to minimize the number of …

Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Semantic memory plays a critical role in reasoning and decision making. It enables an agent to abstract useful knowledge learned from its past experience. Based on an extension of fusion adaptive resonance theory network, this paper presents a novel self-organizing memory model to represent and learn various types of semantic knowledge in a unified manner. The proposed model, called fusion adaptive resonance theory for multimemory learning, incorporates a set of neural processes, through which it may transfer knowledge and cooperate with other long-term memory systems, including episodic memory and procedural memory. Specifically, we present a generic learning process, under which …

Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System, Sungjun Kwon, Dongseok Lee, Jeehoon Kim, Youngki Lee, Seungwoo Kang, Sangwon Seo, Kwangsuk Park

Research Collection School Of Computing and Information Systems

In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user's ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user's high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a …

Iris: Tapping Wearable Sensing To Capture In-Store Retail Insights On Shoppers, Meera Radhakrishnan, Sharanya Eswaran, Archan Misra, Deepthi Chander, Koustuv Dasgupta

Research Collection School Of Computing and Information Systems

We investigate the possibility of using a combination of a smartphone and a smartwatch, carried by a shopper, to get insights into the shopper’s behavior inside a retail store. The proposed IRIS framework uses standard locomotive and gestural micro-activities as building blocks to define novel composite features that help classify different facets of a shopper’s interaction/experience with individual items, as well as attributes of the overall shopping episode or the store. Besides defining such novel features, IRIS builds a novel segmentation algorithm, which partitions the duration of an entire shopping episode into atomic item-level interactions, by using a combination of …

Magi: Enabling Multi-Device Gestural Applications, Tran Huy Vu, Choo Tsu Wei, Kenny, Youngki Lee, Richard Christopher Davis, Archan Misra

Research Collection School Of Computing and Information Systems

We describe our vision of a multiple mobile or wearable device environment and share our initial exploration of our vision in multi-wrist gesture recognition. We explore how multi-device input and output might look, giving four scenarios of everyday multi-device use that show the technical challenges that need to be addressed. We describe our system which allows for recognition to be distributed between multiple devices, fusing recognition streams on a resource-rich device (e.g., mobile phone). An Interactor layer recognises common gestures from the fusion engine, and provides abstract input streams (e.g., scrolling and zooming) to user interface components called Midgets. These …

Improving The Sensitivity Of Unobtrusive Inactivity Detection In Sensor-Enabled Homes For The Elderly, Alvin C. Valera, Hwee-Pink Tan, Liming Bai

Research Collection School Of Computing and Information Systems

Unobtrusive in-home monitoring systems are gaining acceptability and are being deployed to enable relatives and caregivers to remotely monitor and provide timely care to their elderly loved ones or senior clients, respectively, who are living independently. Such systems can provide information about nonmovement or inactivity of the elderly resident. As prolonged inactivity could mean potential danger, several algorithms have been proposed to automatically detect unusually long durations of inactivity. Such schemes, however, suffer from low sensitivity due to their high detection latency. In this paper, we propose Dwell Time-enhanced Dynamic Threshold (DTDT), a scheme for computing adaptive alert thresholds that …

Value-Inspired Service Design In Elderly Home-Monitoring Systems, Na Liu, Sandeep Purao, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

The provision of elderly home-monitoring systems to enhance aging-in-place requires the service to meet the needs of both the elderly and their caregivers. The design of such IT services requires interdisciplinary efforts to look beyond the technical requirements. Taking a value-inspired design perspective, the study argues that service design for promoting aging-in-place needs to reconcile the values of both the elderly and caregivers. Drawn from the framework of basic human values and the unique experience of the SHINESeniors project, the study extracts the core values for elderly and caregivers using a multi-method case analysis. We suggest that both system and …

Did You Take A Break Today? Detecting Playing Foosball Using Your Smartwatch, Sougata Sen, Kiran K. Rachuri, Abhishek Mukherji, Archan Misra

Research Collection School Of Computing and Information Systems

Prolonged working hours are a primary cause of stress, work related injuries (e.g, RSIs), and work-life imbalance in employees at a workplace. As reported by some studies, taking timely breaks from continuous work not only reduces stress and exhaustion but also improves productivity, employee bonding, and camaraderie. Our goal is to build a system that automatically detects breaks thereby assisting in maintaining healthy work-break balance. In this paper, we focus on detecting foosball breaks of employees at a workplace using a smartwatch. We selected foosball as it is one of the most commonly played games at many workplaces in the …

Rack: Automatic Api Recommendation Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo

Research Collection School Of Computing and Information Systems

Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus need carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective code search query is both challenging and time consuming for the developers. In this paper, we propose a novel API recommendation technique -- RACK that recommends a list of relevant APIs for a natural language query for code search by exploiting keyword-API associations from the crowdsourced knowledge of Stack Overflow. We first motivate our technique using an exploratory …

A More Accurate Model For Finding Tutorial Segments Explaining Apis, He Jiang, Jingxuan Zhang, Xiaochen Li, Zhilei Ren, David Lo

Research Collection School Of Computing and Information Systems

Developers prefer to utilize third-party libraries when they implement some functionalities and Application Programming Interfaces (APIs) are frequently used by them. Facing an unfamiliar API, developers tend to consult tutorials as learning resources. Unfortunately, the segments explaining a specific API scatter across tutorials. Hence, it remains a challenging issue to find the relevant segments. In this study, we propose a more accurate model to find the exact tutorial fragments explaining APIs. This new model consists of a text classifier with domain specific features. More specifically, we discover two important indicators to complement traditional text based features, namely co-occurrence APIs and …

A Large Scale Study Of Multiple Programming Languages And Code Quality, Pavneet Singh Kochhar, Withthige Dinusha Ruchira Wijedasa, David Lo

Research Collection School Of Computing and Information Systems

Nowadays, most software use multiple programming languages to implement certain functionalities based on the strengths and weaknesses of different languages. Researchers in the past have studied the impact of independent programming languages on software quality, however, there has been little or no research on the impact of multiple languages on the quality of software. Does the use of multiple languages cause more bugs? Are certain languages when used with other languages make software more bug prone? What are the relationships between multi-language usage and various bug categories? In this study, we perform a large scale empirical investigation to shed light …

An Adaptive Wireless Passive Human Detection Via Fine-Grained Physical Layer Information, Liangyi Gong, Wu Yang, Zimu Zhou, Dapeng Man, Haibin Cai, Xiancun Zhou, Zheng Yang

Research Collection School Of Computing and Information Systems

Wireless device-free passive human detection is a key enabler for a range of indoor location-based services such as asset security, emergency responses, privacy-preserving children and elderly monitoring, etc. Since the feature of received signal varies with different multipath propagation conditions, an labor-intensive on-site calibration procedure is almost indispensable to decide the optimal scenario-specific threshold for human detection. Such overhead, however, impedes readily and fast deployment of wireless device-free human detection systems in practical indoor environments. In this work, we explore PHY layer multipath profiling information to extract a novel quantitative metric Ks as an indicator for link sensitivity, and further …

History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues

Research Collection School Of Computing and Information Systems

Effective automated program repair techniques have great potential to reduce the costs of debugging and maintenance. Previously proposed automated program repair (APR) techniques often follow a generate-and-validate and test- case-driven procedure: They first randomly generate a large pool of fix candidates and then exhaustively validate the quality of the candidates by testing them against existing or provided test suites. Unfortunately, many real-world bugs cannot be repaired by existing techniques even after more than 12 hours of computation in a multi-core cloud environment. More work is needed to advance the capabilities of modern APR techniques. We propose a new technique that …

Towards Improving Interface Modularity In Legacy Java Software Through Automated Refactoring, Raffi T. Khatchadourian, Olivia Moore, Hidehiko Masuhara

Publications and Research

The skeletal implementation pattern is a software design pattern consisting of defining an abstract class that provides a partial interface implementation. However, since Java allows only single class inheritance, if implementers decide to extend a skeletal implementation, they will not be allowed to extend any other class. Also, discovering the skeletal implementation may require a global analysis. Java 8 enhanced interfaces alleviate these problems by allowing interfaces to contain (default) method implementations, which implementers inherit. Java classes are then free to extend a different class, and a separate abstract class is no longer needed; developers considering implementing an interface need …

Requirements Quick Notes, William L. Honig, Shingo Takada

Computer Science: Faculty Publications and Other Works

A short introduction to requirements and their role in system development. Includes industry definition of requirements, overview of basic requirements process including numbering of requirements, ties to testing, and traceability. An introduction to requirements quality attributes (correct, unambiguous, etc.) Includes references to requirements process, numbering, and quality papers.

Requirements Metrics - Definitions Of A Working List Of Possible Metrics For Requirements Quality, William L. Honig

Computer Science: Faculty Publications and Other Works

A work in progress to define a metrics set for requirements. Metrics are defined that apply to either the entire requirements set (requirements document as a whole) or individual atomic (or singular, individual) requirements statements. Requirements are identified with standard names and a identification scheme and include both subjective and objective measures.

An example metric for the full set of requirements: Rd2 - Requirements Consistency, Is the set of atomic requirements internally consistent, with no contradictions, no duplication between individual requirements? An example of a metric for a single requirement: Ra4 - Requirement Verifiability, How adequately can this requirement be …

Human Activity Prediction By Mapping Grouplets To Recurrent Self-Organizing Map, Qianru Sun, Hong Liu, Mengyuan Liu, Tianwei Zhang

Research Collection School Of Computing and Information Systems

Human activity prediction is defined as inferring the high-level activity category with the observation of only a few action units. It is very meaningful for time-critical applications such as emergency surveillance. For efficient prediction, we represent the ongoing human activity by using body part movements and taking full advantage of inherent sequentiality, then find the best matching activity template by a proper aligning measurement.In streaming videos, dense spatio-temporal interest points (STIPs) are first extracted as low-level descriptors for their high detection efficiency. Then, sparse grouplets, i.e., clustered point groups, are located to represent body part movements, for which we propose …

Campus-Scale Mobile Crowd-Tasking: Deployment & Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta

Research Collection School Of Computing and Information Systems

Mobile crowd-tasking markets are growing at an unprecedented rate with increasing number of smartphone users. Such platforms differ from their online counterparts in that they demand physical mobility and can benefit from smartphone processors and sensors for verification purposes. Despite the importance of such mobile crowd-tasking markets, little is known about the labor supply dynamics and mobility patterns of the users. In this paper we design, develop and experiment with a realworld mobile crowd-tasking platform, called TA$Ker. Our contributions are two-fold: (a) We develop TA$Ker, a system that allows us to empirically study the worker responses to push vs. pull …

Ambient And Smartphone Sensor Assisted Adl Recognition In Multi-Inhabitant Smart Environments, Nirmalya Roy, Archan Misra, Diane Cook

Research Collection School Of Computing and Information Systems

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users’ spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user …

Ibed: Combining Ibea And De For Optimal Feature Selection In Software Product Line Engineering, Yinxing Xue, Jinghui Zhong, Tian Huat Tan, Yang Liu, Wentong Cai, Manman Chen, Jun Sun

Research Collection School Of Computing and Information Systems

Software configuration, which aims to customize the software for different users (e.g., Linux kernel configuration), is an important and complicated task. In software product line engineering (SPLE), feature oriented domain analysis is adopted and feature model is used to guide the configuration of new product variants. In SPLE, product configuration is an optimal feature selection problem, which needs to find a set of features that have no conflicts and meanwhile achieve multiple design objectives (e.g., minimizing cost and maximizing the number of features). In previous studies, several multi-objective evolutionary algorithms (MOEAs) were used for the optimal feature selection problem and …