Software Engineering Commons^™

Cora: Commingled Remains And Analytics – An Open Community Ecosystem, Nicole Mcelroy, Ryan Ernst

UNO Student Research and Creative Activity Fair

Anthropologists at organizations such as the DPAA (Defense POW/MIA Accounting Agency) have the tough job of sorting through commingled remains of fallen soldiers. Under the direction of Professor Pawaskar at the College of IS&T, Ryan Ernst and I are currently developing a web application for the DPAA that will help them inventory the bones and record all the appropriate associations. After the inventory web application is built we will begin the analysis process using graph theory and other mathematical algorithms. This will ultimately help organizations like the DPAA get closer to the end goal of identifying fallen soldiers from commingled …

Crowdservice: Optimizing Mobile Crowdsourcing And Service Composition, Xin Peng, Jingxiao Gu, Tian Huat Tan, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao Zhao

Research Collection School Of Computing and Information Systems

Some user needs can only be met by leveraging the capabilities of others to undertake particular tasks that require intelligence and labor. Crowdsourcing such capabilities is one way to achieve this. But providing a service that leverages crowd intelligence and labor is a challenge, since various factors need to be considered to enable reliable service provisioning. For example, the selection of an optimal set of workers from those who bid to perform a task needs to be made based on their reliability, expected reward, and distance to the target locations. Moreover, for an application involving multiple services, the overall cost …

An Empirical Study Of Css Code Smells In Web Frameworks, Tobias Paul Bleisch

Master's Theses

Cascading Style Sheets (CSS) has become essential to front-end web development for the specification of style. But despite its simple syntax and the theoretical advantages attained through the separation of style from content and behavior, CSS authoring today is regarded as a complex task. As a result, developers are increasingly turning to CSS preprocessor languages and web frameworks to aid in development. However, previous studies show that even highly popular websites which are known to be developed with web frameworks contain CSS code smells such as duplicated rules and hard-coded values. Such code smells have the potential to cause adverse …

Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade off-amenable …

Engagemon: Multi-Modal Engagement Sensing For Mobile Games, Sinh Huynh, Seungmin Kim, Jeonggil Ko, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Understanding the engagement levels players have with a game is a useful proxy for evaluating the game design and user experience. This is particularly important for mobile games as an alternative game is always just an easy download away. However, engagement is a subjective concept and usually requires fine-grained highly disruptive interviews or surveys to determine accurately. In this paper, we present EngageMon, a first-of-its-kind system that uses a combination of sensors from the smartphone (touch events), a wristband (photoplethysmography and electrodermal activity sensor readings), and an external depth camera (skeletal motion information) to accurately determine the engagement level of …

Visualizing Research Impact Through Citation Data, Yong Wang, Conglei Shi, Liangyue Li, Hanghang Tong, Huamin Qu

Research Collection School Of Computing and Information Systems

Research impact plays a critical role in evaluating the research quality and influence of a scholar, a journal, or a conference. Many researchers have attempted to quantify research impact by introducing different types of metrics based on citation data, such as h-index, citation count, and impact factor. These metrics are widely used in the academic community. However, quantitative metrics are highly aggregated in most cases and sometimes biased, which probably results in the loss of impact details that are important for comprehensively understanding research impact. For example, which research area does a researcher have great research impact on? How does …

W-Air: Enabling Personal Air Pollution Monitoring On Wearables, Balz Maag, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Accurate, portable and personal air pollution sensing devices enable quantification of individual exposure to air pollution, personalized health advice and assistance applications. Wearables are promising (e.g., on wristbands, attached to belts or backpacks) to integrate commercial off-the-shelf gas sensors for personal air pollution sensing. Yet previous research lacks comprehensive investigations on the accuracies of air pollution sensing on wearables. In response, we proposed W-Air, an accurate personal multi-pollutant monitoring platform for wearables. We discovered that human emissions introduce non-linear interference when low-cost gas sensors are integrated into wearables, which is overlooked in existing studies. W-Air adopts a sensor-fusion calibration scheme …

A New Revocable And Re-Delegable Proxy Signature And Its Application, Shengmin Xu, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

With the popularity of cloud computing and mobile Apps, on-demand services such as on-line music or audio streaming and vehicle booking are widely available nowadays. In order to allow efficient delivery and management of the services, for large-scale on-demand systems, there is usually a hierarchy where the service provider can delegate its service to a top-tier (e.g., countrywide) proxy who can then further delegate the service to lower level (e.g., region-wide) proxies. Secure (re-)delegation and revocation are among the most crucial factors for such systems. In this paper, we investigate the practical solutions for achieving re-delegation and revocation utilizing proxy …

A Call To Promote Soft Skills In Software Engineering, Luiz Fernando Capretz, Fahem Ahmed

Electrical and Computer Engineering Publications

We have been thinking about other aspects of software engineering for many years; the missing link in engineering software is the soft skills set, essential in the software development process. Although soft skills are among the most important aspects in the creation of software, they are often overlooked by educators and practitioners. One of the main reasons for the oversight is that soft skills are usually related to social and personality factors, i.e., teamwork, motivation, commitment, leadership, multi-culturalism, emotions, interpersonal skills, etc. This editorial is a manifesto declaring the importance of soft skills in software engineering with the intention to …

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. …

Early Detection Of Mild Cognitive Impairment In Elderly Through Iot: Preliminary Findings, Hwee-Xian Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Mild Cognitive Impairment (MCI) results in the gradual decline in a person’s cognitive abilities, and subsequently an increased risk of developing dementia. Although there is no cure for dementia, timely medical and clinical interventions can be administered to elderly who have been diagnosed with MCI, to decelerate the process of further cognitive decline and prolong the duration that they enjoy quality of life. In this paper, we present our preliminary findings of early detection of MCI in elderly who are living in the community, through the use of Internet of Things (IoT) devices for continuous, unobtrusive sensing. Multimodal sensors are …

Technologies For Ageing-In-Place: The Singapore Context, Nadee Goonawardene, Pius Lee, Hwee Xian Tan, Alvin C. Valera, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

The number of elderly citizens aged 65 and above in Singapore, is expected to double from 440,000in 2015, to 900,000 by 2030. Along with this “Silver Tsunami” is the upward trend of the numberof elderly who are living alone — which is estimated to increase from 35,000 in 2012 to 83,000 by2030. These exclude elderly who are alone at home when their family members are working.Elderly who are staying alone are at higher risk of social isolation and tend to have poorer accessto healthcare. In addition, the general elderly population is typically more susceptible to deteriorating health conditions, which can …

Vt-Revolution: Interactive Programming Video Tutorial Authoring And Watching System, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

Procedural knowledge describes actions and manipulations that are carried out to complete programming tasks. An effective way to document procedural knowledge is programming video tutorials. Existing solutions to adding interactive workflow and elements to programming videos have a dilemma between the level of desired interaction and the efforts required for authoring tutorials. In this work, we tackle this dilemma by designing and building a programming video tutorial authoring system that leverages operating system level instrumentation to log workflow history while tutorial authors are creating programming videos, and the corresponding tutorial watching system that enhances the learning experience of video tutorials …

Cross-Language Learning For Program Classification Using Bilateral Tree-Based Convolutional Neural Networks, Duy Quoc Nghi Bui, Lingxiao Jiang, Yijun Yu

Research Collection School Of Computing and Information Systems

Towards the vision of translating code that implements an algorithm from one programming language into another, this paper proposes an approach for automated program classification using bilateral tree-based convolutional neural networks (BiTBCNNs). It is layered on top of two tree-based convolutional neural networks (TBCNNs), each of which recognizes the algorithm of code written in an individual programming language. The combination layer of the networks recognizes the similarities and differences among code in different programming languages. The BiTBCNNs are trained using the source code in different languages but known to implement the same algorithms and/or functionalities. For a preliminary evaluation, we …

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), …

The Accuracy, Fairness, And Limits Of Predicting Recidivism, Julie Dressel, Hany Farid

Dartmouth Scholarship

Algorithms for predicting recidivism are commonly used to assess a criminal defendant’s likelihood of committing a crime. These predictions are used in pretrial, parole, and sentencing decisions. Proponents of these systems argue that big data and advanced machine learning make these analyses more accurate and less biased than humans. We show, however, that the widely used commercial risk assessment software COMPAS is no more accurate or fair than predictions made by people with little or no criminal justice expertise. We further show that a simple linear predictor provided with only two features is nearly equivalent to COMPAS with its 137 …

A Malware Analysis And Artifact Capture Tool, Dallas Wright, Josh Stroschein

Research & Publications

Malware authors attempt to obfuscate and hide their code in its static and dynamic states. This paper provides a novel approach to aid analysis by intercepting and capturing malware artifacts and providing dynamic control of process flow. Capturing malware artifacts allows an analyst to more quickly and comprehensively understand malware behavior and obfuscation techniques and doing so interactively allows multiple code paths to be explored. The faster that malware can be analyzed the quicker the systems and data compromised by it can be determined and its infection stopped. This research proposes an instantiation of an interactive malware analysis and artifact …

Algorithmic Music Generation For Pedagogy Of Sight Reading, Ryan Stephen Davis

Electronic Theses and Dissertations

Autodeus is the name of the program that has been developed and was designed to aid guitar students in the attainment and betterment of musical notation sight reading skills. Its primary goal is to provide a very flexible tool that has the ability to generate virtually endless types of sight reading exercises at many various skill levels.

A complimentary 2 year-long comprehensive guitar sight-reading course syllabus can be implemented via Autodeus as it is capable of generating all the necessary exercises. It is able to generate these exercises quickly and efficiently through the use of a back tracking algorithm that …

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 …

On The Effectiveness Of Generic Malware Models, Naman Bagga, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

Malware detection based on machine learning typically involves training and testing models for each malware family under consideration. While such an approach can generally achieve good accuracy, it requires many classification steps, resulting in a slow, inefficient, and potentially impractical process. In contrast, classifying samples as malware or benign based on more generic “families” would be far more efficient. However, extracting common features from extremely general malware families will likely result in a model that is too generic to be useful. In this research, we perform controlled experiments to determine the tradeoff between generality and accuracy—over a variety of machine …