Software Engineering Commons^™

Identifying Self-Admitted Technical Debt In Open Source Projects Using Text Mining, Qiao Huang, Emad Shihab, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Technical debt is a metaphor to describe the situation in which long-term code quality is traded for short-term goals in software projects. Recently, the concept of self-admitted technical debt (SATD) was proposed, which considers debt that is intentionally introduced, e.g., in the form of quick or temporary fixes. Prior work on SATD has shown that source code comments can be used to successfully detect SATD, however, most current state-of-the-art classification approaches of SATD rely on manual inspection of the source code comments. In this paper, we proposed an automated approach to detect SATD in source code comments using text mining. …

Things You May Not Know About Android (Un)Packers: A Systematic Study Based On Whole-System Emulation, Yue Duan, Mu Zhang, Abhishek Vasist Bhaskar, Heng Yin, Xiaorui Pan, Tongxin Li, Xueqiang Wang, Xiaofeng Wang

Research Collection School Of Computing and Information Systems

The prevalent usage of runtime packers has complicated Android malware analysis, as both legitimate and malicious apps are leveraging packing mechanisms to protect themselves against reverse engineer. Although recent efforts have been made to analyze particular packing techniques, little has been done to study the unique characteristics of Android packers. In this paper, we report the first systematic study on mainstream Android packers, in an attempt to understand their security implications. For this purpose, we developed DROIDUNPACK, a whole-system emulation based Android packing analysis framework, which compared with existing tools, relies on intrinsic characteristics of Android runtime (rather than heuristics), …

Support Vector Machines For Image Spam Analysis, Aneri Chavda, Katerina Potika, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

Email is one of the most common forms of digital communication. Spam is unsolicited bulk email, while image spam consists of spam text embedded inside an image. Image spam is used as a means to evade text-based spam filters, and hence image spam poses a threat to email-based communication. In this research, we analyze image spam detection using support vector machines (SVMs), which we train on a wide variety of image features. We use a linear SVM to quantify the relative importance of the features under consideration. We also develop and analyze a realistic “challenge” dataset that illustrates the limitations …

Automating Ciri Ratings Of Human Rights Reports Using Gate, Joshua M. Joiner

UNF Graduate Theses and Dissertations

This thesis involves parsing document-based reports from the United States Human Rights Reports and rating the human practices for various countries based on the CIRI (Cingranelli-Richards) Human Rights Data Project dataset. The United States Human Rights Reports are annual reports that cover internationally recognized human rights practices regarding individual, civil, political, and worker rights. Students, scholars, policymakers, and analysts used the CIRI data for practical and research purposes. CIRI analyzed the annual reports from 1981 to 2011 and then stopped releasing the dataset for any further years, but a possible reason is due to the manual process of scouring the …

Ransomware Behavioural Analysis On Windows Platforms, Nikolai Hampton, Zubair A. Baig, Sherali Zeadally

Research outputs 2014 to 2021

Ransomware infections have grown exponentially during the recent past to cause major disruption in operations across a range of industries including the government. Through this research, we present an analysis of 14 strains of ransomware that infect Windows platforms, and we do a comparison of Windows Application Programming Interface (API) calls made through ransomware processes with baselines of normal operating system behaviour. The study identifies and reports salient features of ransomware as referred through the frequencies of API calls

Smart-Teleprompter: An Online Teleprompter With Text Editing, Mikyla Wilfred

Williams Honors College, Honors Research Projects

Mikyla Wilfred

Major: Computer Science

Project Sponsor: Dr. Collard

Number of Project Credits: 3

Smart-Teleprompter

The smart-teleprompter is a website that allows a logged in user to edit text files as well as teleprompt them straight to the screen. A teleprompter is used by newscasters and other media professionals to read scripts while still looking at or near the camera. My project uses this concept creating a page that defaults to white font on a black background that can scroll through the script. The website allows the logged in user to save defaults of font color, background color, font style …

Exercising Efficiently With An Equipment Ticketing Mobile Application, Eric Merryman

Williams Honors College, Honors Research Projects

The purpose of this project is to explore the discipline of developing mobile applications using a cross-platform framework. Mobile devices have had a large influence on our lifestyles and with the global mobile application market grossing billions of dollars, many companies are adapting to the change and creating mobile applications for their business. With a variety of competing mobile devices and operating systems, companies must cater to each system. Cross-platform frameworks allow developers to quickly create mobile applications that can be used on many different devices. Xamarin.Forms is a cross-platform framework that allows developers to create a mobile application using …

Exact And Heuristic Approaches For The Multi-Agent Orienteering Problem With Capacity Constraints, Wenjie Wang, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This paper introduces and addresses a new multiagent variant of the orienteering problem (OP), namely the multi-agent orienteering problem with capacity constraints (MAOPCC). Different from the existing variants of OP, MAOPCC allows a group of visitors to concurrently visit a node but limits the number of visitors simultaneously being served at each node. In this work, we solve MAOPCC in a centralized manner and optimize the total collected rewards of all agents. A branch and bound algorithm is first proposed to find an optimal MAOPCC solution. Since finding an optimal solution for MAOPCC can become intractable as the number of …

Skylens: Visual Analysis Of Skyline On Multi-Dimensional Data, Xun Zhao, Yanhong Wu, Weiwei Cui, Xinnan Du, Yuan Chen, Yong Wang, Dik Lun Lee, Huamin Qu

Research Collection School Of Computing and Information Systems

Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e.. the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points …

Smart Monitoring Via Participatory Ble Relaying, Meeralakshmi Radhakrishnan, Sougata Sen, Archan Misra, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

We espouse the vision of a smart object/campus architecture where sensors attached to smart objects use BLE as communication interface, and where smartphones act as opportunistic relays to transfer the data. We explore the feasibility of the vision with real-world Wi-Fi based location traces from our university campus. Our feasibility studies establish that redundancy exists in user movement within the indoor spaces, and that this redundancy can be exploited for collecting sensor data in an opportunistic, yet fair manner. We develop a couple of alternative heuristics that address the BLE energy asymmetry challenge by intelligently duty-cycling the scanning actions of …

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

Secure Server-Aided Top-K Monitoring, Yujue Wang, Hwee Hwa Pang, Yanjiang Yang, Xuhua Ding

Research Collection School Of Computing and Information Systems

In a data streaming model, a data owner releases records or documents to a set of users with matching interests, in such a way that the match in interest can be calculated from the correlation between each pair of document and user query. For scalability and availability reasons, this calculation is delegated to third-party servers, which gives rise to the need to protect the integrity and privacy of the documents and user queries. In this paper, we propose a server-aided data stream monitoring scheme (DSM) to address the aforementioned integrity and privacy challenges, so that the users are able to …

D-Watch: Embracing “Bad” Multipaths For Device-Free Localization With Cots Rfid Devices, Ju Wang, Jie Xiong, Hongbo Jiang, Xiaojiang Chen, Dingyi Fang

Research Collection School Of Computing and Information Systems

Device-free localization, which does not require any device attached to the target, is playing a critical role in many applications, such as intrusion detection, elderly monitoring and so on. This paper introduces D-Watch, a device-free system built on the top of low cost commodity-off-the-shelf RFID hardware. Unlike previous works which consider multipaths detrimental, D-Watch leverages the ''bad'' multipaths to provide a decimeter-level localization accuracy without offline training. D-Watch harnesses the angle-of-arrival information from the RFID tags' backscatter signals. The key intuition is that whenever a target blocks a signal's propagation path, the signal power experiences a drop which can be …

Robust Human Activity Recognition Using Lesser Number Of Wearable Sensors, Di Wang, Edwin Candinegara, Junhui Hou, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

In recent years, research on the recognition of human physical activities solely using wearable sensors has received more and more attention. Compared to other types of sensory devices such as surveillance cameras, wearable sensors are preferred in most activity recognition applications mainly due to their non-intrusiveness and pervasiveness. However, many existing activity recognition applications or experiments using wearable sensors were conducted in the confined laboratory settings using specifically developed gadgets. These gadgets may be useful for a small group of people in certain specific scenarios, but probably will not gain their popularity because they introduce additional costs and they are …

Eeg-Based Emotion Recognition Via Fast And Robust Feature Smoothing, Cheng Tang, Di Wang, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

Electroencephalograph (EEG) signals reveal much of our brain states and have been widely used in emotion recognition. However, the recognition accuracy is hardly ideal mainly due to the following reasons: (i) the features extracted from EEG signals may not solely reflect one’s emotional patterns and their quality is easily affected by noise; and (ii) increasing feature dimension may enhance the recognition accuracy, but it often requires extra computation time. In this paper, we propose a feature smoothing method to alleviate the aforementioned problems. Specifically, we extract six statistical features from raw EEG signals and apply a simple yet cost-effective feature …

Answerbot: Automated Generation Of Answer Summary To Developers’ Technical Questions, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

The prevalence of questions and answers on domain-specific Q&A sites like Stack Overflow constitutes a core knowledge asset for software engineering domain. Although search engines can return a list of questions relevant to a user query of some technical question, the abundance of relevant posts and the sheer amount of information in them makes it difficult for developers to digest them and find the most needed answers to their questions. In this work, we aim to help developers who want to quickly capture the key points of several answer posts relevant to a technical question before they read the details …

Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang

Research Collection School Of Computing and Information Systems

Target imaging and material identification play an important role in many real-life applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commercial of-the-shelf (COTS) RFID devices. The key intuition is that different materials and target sizes cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system including (i) indoor environments exhibit rich multipath which breaks the linear relationship between …

Understanding Stack Overflow Code Fragments, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Code fragments posted in answers on Q&A forums can form an important source of developer knowledge. However, effective reuse of code fragments found online often requires information other than the code fragment alone. We report on the results of a survey-based study to investigate to what extent developers perceive Stack Overflow code fragments to be self-explanatory. As part of the study, we also investigated the types of information missing from fragments that were not self-explanatory. We find that less than half of the Stack Overflow code fragments in our sample are considered to be self-explanatory by the 321 participants who …

Clsters: A General System For Reducing Errors Of Trajectories Under Challenging Localization Situations, Hao Wu, Weiwei Sun, Baihua Zheng, Li Yang, Wei Zhou

Research Collection School Of Computing and Information Systems

Trajectory data generated by outdoor activities have great potential for location based services. However, depending on the localization technique used, certain trajectory data could contain large errors. For example, the error of trajectories generated by cellular-based localization techniques is around 100m which is ten times larger than that of GPS-based trajectories. Hence, enhancing the utility of those large-error trajectories becomes a challenge. In this paper we show how to improve the quality of trajectory data having large errors. Some existing works reduce the error through hardware which requires information such as the time of arrival (TOA), received signal strength indication …

On-Demand Developer Documentation, Martin P. Robillard, Andrian Marcus, Christoph Treude, Gabriele Bavota, Oscar Chaparro, Neil Ernst, Marco Aurélio Gerosa, Michael Godfrey, Michele Lanza, Mario Linares-Vasquez, Gail C. Murphy, Laura Moreno, David Shepherd, Edmund Wong

Research Collection School Of Computing and Information Systems

We advocate for a paradigm shift in supporting the information needs of developers, centered around the concept of automated on-demand developer documentation. Currently, developer information needs are fulfilled by asking experts or consulting documentation. Unfortunately, traditional documentation practices are inefficient because of, among others, the manual nature of its creation and the gap between the creators and consumers. We discuss the major challenges we face in realizing such a paradigm shift, highlight existing research that can be leveraged to this end, and promote opportunities for increased convergence in research on software documentation.

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Ehealthportal: A Social Support Hub For The Active Living Of The Elderly, Di Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The absolute and relative increases in the number of elderly are evident worldwide, from the most developed countries to the lowest-income regions. The fast demographic transition poses great challenges to the healthcare system and introduces a significant burden to the elderly and their family. To meet the unprecedented challenges of global aging, various aging-in-place (AIP) solutions have been proposed to enable the elderly to live in their own home and community safely, independently and comfortably. Elderly need support in various aspects, such as physical, cognitive, emotional, and social, in their daily life. However, most existing AIP solutions provide support in …

Elderly Friendliness Evaluation Of Mobile Assistants, Di Wang, Xinjia Yu, Simon Fauvel, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

The rapidly increasing elderly population in many developed and developing countries poses great challenges to elderly care systems. To alleviate the problem of a shrinking workforce to deliver elderly care, using mobile intelligent assistants to lessen the caregivers' workload becomes a promising solution. However, the friendliness of such mobile assistants, which is seldom measured in a quantitative manner, may hinder their acceptance by the elderly users. In this paper, we propose a formalized systematic approach named Elderly Friendliness Evaluation Methodology (EFEM) to measure the elderly friendliness of any product, service or system. Furthermore, we apply EFEM to evaluate the elderly …

Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson

Research Collection School Of Computing and Information Systems

No abstract provided.

Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee

Research Collection School Of Computing and Information Systems

It is essential to proactively detect mental health problems such as loneliness and depression in the independently-living elderly for timely intervention by caregivers. In this paper, we introduce an unobtrusive sensor-enabled monitoring system that has been deployed to 50 government housing ats with the independent-living elderly for two years. Then, we also present our initial findings from the 6-month sensor data between August 2015 and April 2016 as well as the survey data to measure the subjective well-being indicator. Our study showed the promising results that "room-level movements within a house" and "going out" behavior captured by our simple sensor …

Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su

Research Collection School Of Computing and Information Systems

Android allows applications to communicate with system service via system service helper so that applications can use various functions wrapped in the system services. Meanwhile, system services leverage the service helpers to enforce security mechanisms, e.g. input parameter validation, to protect themselves against attacks. However, service helpers can be easily bypassed, which poses severe security and privacy threats to system services, e.g., privilege escalation, function execution without users’ interactions, system service crash, and DoS attacks. In this paper, we perform the first systematic study on such vulnerabilities and investigate their impacts. We develop a tool to analyze all system services …

Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen

Research Collection School Of Computing and Information Systems

Many real applications in real-time news stream advertising call for efficient processing of long queriesagainst short text. In such applications, dynamic news feeds are regarded as queries to match against anadvertisement (ad) database for retrieving the k most relevant ads. The existing approaches to keywordretrieval cannot work well in this search scenario when queries are triggered at a very high frequency.To address the problem, we introduce new techniques to significantly improve search performance. First,we devise a two-level partitioning for tight upper bound estimation and a lazy evaluation scheme to delayfull evaluation of unpromising candidates, which can bring three to four …

Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler

Research Collection School Of Computing and Information Systems

The PART-WHOLE relationship routinely finds itself in many disciplines, ranging from collaborative teams, crowdsourcing, autonomous systems to networked systems. From the algorithmic perspective, the existing work has primarily focused on predicting the outcomes of the whole and parts, by either separate models or linear joint models, which assume the outcome of the parts has a linear and independent effect on the outcome of the whole. In this paper, we propose a joint predictive method named PAROLE to simultaneously and mutually predict the part and whole outcomes. The proposed method offers two distinct advantages over the existing work. First (Model Generality), …

An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo

Research Collection School Of Computing and Information Systems

Web APIs provide various functionalities that can be leveraged by developers in building their applications. ProgrammableWeb, which is the largest and most active web API and mashup collection, provides a record of thousands of web APIs and mashups. However, important properties about these large number of web APIs, such as their functionality and support/resources for learning, have never been studied by the existing research work. In this study, we perform an exploratory analysis on functionality and learning resources of 9,883 web APIs and 4,315 mashups listed on ProgrammableWeb, and find that: (1) web APIs provide a wide range of functionalities …

Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users …