Software Engineering Commons^™

Applications Of Varying Leadership Structures For Software Engineering Teams, Elliot Sandfort

Honors Program: Senior Projects (Public)

This thesis explores the similarities and differences between applications of managing software engineering teams in Design Studio and the state of the practice. Information about the leadership structure of Design Studio teams was gathered over 3 semesters of Design Studio experiences with two companies: Hudl and TD Ameritrade. Information about leadership concepts in the state of the practice was gathered from experiences and observations with three different companies: Hudl, Garmin, and TD Ameritrade. From these experiences and observations, it can be concluded that the leadership structure of Design Studio is valuable as a student learning experience, and with proper consideration …

Ksugo, Chase Godwin

KSU Journey Honors College Capstones and Theses

KSUGo seeks to better enable students to interact with their community, maintain a level of safety on and off campus, improve their course management skills, and increase information propagation among students and campus officials. Currently, Kennesaw State does not have a dedicated general purpose native application on any mobile device platform for students, faculty, or staff to use for improving their everyday Kennesaw State experience. This project seeks to rectify that need by providing a native application with support for the Android platform.

Recommending Apis For Software Evolution, Ferdian Thung

Dissertations and Theses Collection (Open Access)

Softwares are constantly evolving. This evolution has been made easier through the use of Application Programming Interfaces (APIs). By leveraging APIs, developers reuse previously implemented functionalities and concentrate on writing new codes. These APIs may originate from either third parties or internally from other compo- nents of the software that are currently developed. In the first case, developers need to know how to find and use third party APIs. In the second case, developers need to be aware of internal APIs in their own software. In either case, there is often too much information to digest. For instance, finding the …

Anflo: Detecting Anomalous Sensitive Information Flows In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Smartphone apps usually have access to sensitive user data such as contacts, geo-location, and account credentials and they might share such data to external entities through the Internet or with other apps. Confidentiality of user data could be breached if there are anomalies in the way sensitive data is handled by an app which is vulnerable or malicious. Existing approaches that detect anomalous sensitive data flows have limitations in terms of accuracy because the definition of anomalous flows may differ for different apps with different functionalities; it is normal for “Health” apps to share heart rate information through the Internet …

Finding Small-Bowel Lesions: Challenges In Endoscopy-Image-Based Learning Systems, Jungmo Ahn, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee, Jeonggil Ko

Research Collection School Of Computing and Information Systems

Capsule endoscopy identifies damaged areas in a patient's small intestine but often outputs poor-quality images or misses lesions, leading to either misdiagnosis or repetition of the lengthy procedure. The authors propose applying deep-learning models to automatically process the captured images and identify lesions in real time, enabling the capsule to take additional images of a specific location, adjust its focus level, or improve image quality. The authors also describe the technical challenges in realizing a viable automated capsule-endoscopy system.

Wisdom In Sum Of Parts: Multi-Platform Activity Prediction In Social Collaborative Sites, Roy Ka-Wei Lee, David Lo

Research Collection School Of Computing and Information Systems

In this paper, we proposed a novel framework which uses user interests inferred from activities (a.k.a., activity interests) in multiple social collaborative platforms to predict users’ platform activities. Included in the framework are two prediction approaches: (i) direct platform activity prediction, which predicts a user’s activities in a platform using his or her activity interests from the same platform (e.g., predict if a user answers a given Stack Overflow question using the user’s interests inferred from his or her prior answer and favorite activities in Stack Overflow), and (ii) cross-platform activity prediction, which predicts a user’s activities in a platform …

Analyzing Requirements And Traceability Information To Improve Bug Localization, Michael Rath, David Lo, Patrick Mader

Research Collection School Of Computing and Information Systems

Locating bugs in industry-size software systems is time consuming and challenging. An automated approach for assisting the process of tracing from bug descriptions to relevant source code benefits developers. A large body of previous work aims to address this problem and demonstrates considerable achievements. Most existing approaches focus on the key challenge of improving techniques based on textual similarity to identify relevant files. However, there exists a lexical gap between the natural language used to formulate bug reports and the formal source code and its comments. To bridge this gap, state-of-the-art approaches contain a component for analyzing bug history information …

Recommending Frequently Encountered Bugs, Yun Zhang, David Lo, Xin Xia, Jing Jiang, Jianling Sun

Research Collection School Of Computing and Information Systems

Developers introduce bugs during software development which reduce software reliability. Many of these bugs are commonly occurring and have been experienced by many other developers. Informingdevelopers, especially novice ones, about commonly occurring bugsin a domain of interest (e.g., Java), can help developers comprehendprogram and avoid similar bugs in the future. Unfortunately, information about commonly occurring bugs are not readily available. Toaddress this need, we propose a novel approach named RFEB whichrecommends frequently encountered bugs (FEBugs) that may affectmany other developers. RFEB analyzes Stack Overflow which is thelargest software engineering-specific Q&A communities. Amongthe plenty of questions posted in Stack Overflow, many …

Deep Code Comment Generation, Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin

Research Collection School Of Computing and Information Systems

During software maintenance, code comments help developerscomprehend programs and reduce additional time spent on readingand navigating source code. Unfortunately, these comments areoften mismatched, missing or outdated in the software projects.Developers have to infer the functionality from the source code.This paper proposes a new approach named DeepCom to automatically generate code comments for Java methods. The generatedcomments aim to help developers understand the functionalityof Java methods. DeepCom applies Natural Language Processing(NLP) techniques to learn from a large code corpus and generatescomments from learned features. We use a deep neural networkthat analyzes structural information of Java methods for bettercomments generation. We conduct …

Learning From Mutants: Using Code Mutation To Learn And Monitor Invariants Of A Cyber-Physical System, Yuqi Chen, Christopher M. Poskitt, Jun Sun

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPS) consist of sensors, actuators, and controllers all communicating over a network; if any subset becomes compromised, an attacker could cause significant damage. With access to data logs and a model of the CPS, the physical effects of an attack could potentially be detected before any damage is done. Manually building a model that is accurate enough in practice, however, is extremely difficult. In this paper, we propose a novel approach for constructing models of CPS automatically, by applying supervised machine learning to data traces obtained after systematically seeding their software components with faults ("mutants"). We demonstrate the …

Sotorrent: Reconstructing And Analyzing The Evolution Of Stack Overflow Posts, Sebastian Baltes, Lorik Dumani, Christoph Treude, Stephan Diehl

Research Collection School Of Computing and Information Systems

Stack Overflow (SO) is the most popular question-and-answer website for software developers, providing a large amount of code snippets and free-form text on a wide variety of topics. Like other software artifacts, questions and answers on SO evolve over time, for example when bugs in code snippets are fixed, code is updated to work with a more recent library version, or text surrounding a code snippet is edited for clarity. To be able to analyze how content on SO evolves, we built SOTorrent, an open dataset based on the official SO data dump. SOTorrent provides access to the version history …

Budgeting In Student Life: An Educational Website, Heather Grunden

Honors Projects

An applied honors project in the form of a website prototype. The purpose of this website is to introduce college students to the concept of budgeting and to teach them the core steps of creating their own budget, since many existing budgeting applications are pay-to-use, and the free options tend to have little to no instruction.

Fit Buddy Prototype And Ksugo Mobile App, Albert Lim

KSU Journey Honors College Capstones and Theses

The purpose of my Honors Capstone project is to deliver a mobile app prototype that is focused on improving the student experience at Kennesaw State University (KSU), called Fit Buddy. There are three key concepts that will be covered in this Proof of Concept project: social networking, fitness, and IoT (Internet of Things) usages.

Additionally, the purpose of the CS Capstone project is to deliver a mobile app that is focused on improving the faculty, student, and guest experience at KSU, called KSUGo. The primary objective and purpose in creating this stems from KSU’s many resourceful outlets, which we seek …

Creating A Reproducible Metadata Transformation Pipeline Using Technology Best Practices, Cara Key, Mike Waugh

Digital Initiatives Symposium

Over the course of two years, a team of librarians and programmers from LSU Libraries migrated the 186 collections of the Louisiana Digital Library from OCLC's CONTENTdm platform over to the open-source Islandora platform.

Early in the process, the team understood the value of creating a reproducible metadata transformation pipeline, because there were so many unknowns at the beginning of the process along with the certainty that mistakes would be made. This presentation will describe how the team used innovative and collaborative tools, such as Trello, Ansible, Vagrant, VirtualBox, git and GitHub to accomplish the task.

Seismology And Volcanology: Exploration Of Volcanoes, Long-Periods, And Machines - Predicting Volcano Eruption Using Signature Seismic Data, Kyle Killion, Rajeev Kumar, Celia J. Taylor, Gabriele Morra

SMU Data Science Review

Abstract. Seismo-volcanologists manually isolate and verify long-period waves and Strombolian events using seismic and acoustic waves. This is a very detailed and time-consuming process. This project is to employ machine learning algorithms to find models which locate long-period and Strombolian signatures automatically. By comparing the timing of seismic and acoustic waves, clustering techniques effectively isolated big volcanic events and aided in the further refinement of techniques to capture the hundreds of typical daily Strombolian events at Villarrica volcano. Within the research, we utilized the unsupervised machine learning environment to locate a group of signatures for customizing machine learned long-period signature …

Lee Honors College Mobile Application, James Ward

Honors Theses

In the spring of 2018 three Computer Science students Benjamin Campbell, James Ward, and Peter Shutt created a mobile application. This app was developed over the span of two semesters for their senior design project; a capstone to their degrees.

Their client, The Lee Honors College at Western Michigan University --referred to as LHC and WMU respectively hereafter-- has a plethora of academic and social information, and a large demand for access to it. This information includes building hours, contact information, health resources, a LHC specific course catalog, social media posts, event descriptions, and much more. The volume of information, …

Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

Providing secure access to smart devices such as mobiles, wearables and various other IoT devices is becoming increasinglyimportant, especially as these devices store a range of sensitive personal information. Breathing acoustics-based authentication offers a highly usable and possibly a secondary authentication mechanism for such authorized access, especially as it canbe readily applied to small form-factor devices. Executing sophisticated machine learning pipelines for such authenticationon such devices remains an open problem, given their resource limitations in terms of storage, memory and computational power. To investigate this possibility, we compare the performance of an end-to-end system for both user identification anduser verification …

Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi Khatchadourian, Hidehiko Masuhara

Publications and Research

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations …

Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi Khatchadourian, Hidehiko Masuhara

Publications and Research

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations …

Using Github In Large Software Engineering Classes: An Exploratory Case Study, Miroslav Tushev

LSU Master's Theses

GitHub has been recently used in Software Engineering (SE) classes to facilitate col- laboration in student team projects. The underlying tenet is that the technical and social feature of GitHub can help students to communicate and collaborate more effectively as a team as well as help teachers to evaluate individual student contribution more objectively. To shed more light on this, in this case study, we explore the benefits and drawbacks of using GitHub in SE classes. Our study is conducted in a software engineering class of 91 students divided into 18 teams. Our research method includes an entry and an …

Technological Evolution In Software Engineering, Cody Miller

Engineering and Technology Management Student Projects

In all software development processes, the software must evolve in response to its environment or user needs to maintain satisfactory performance. If software doesn’t support change, it gradually becomes useless. With many organizations today, being software-centric organizations, this has huge implications for their business: evolve your software, or risk your software becoming gradually useless, and therefore, your entire business.

Technology Evolution is a highly relevant subject, Intel’s business model for the last 50 years, has been that of Moore’s Law, a hardware centric Technology Evolution model. As a Software Engineer at Intel, our business group faces a similar issue, we …

Domain-Specific Cross-Language Relevant Question Retrieval, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Chinese developers often cannot effectively search questions in English, because they may have difficulties in translating technical words from Chinese to English and formulating proper English queries. For the purpose of helping Chinese developers take advantage of the rich knowledge base of Stack Overflow and simplify the question retrieval process, we propose an automated cross-language relevant question retrieval (CLRQR) system to retrieve relevant English questions for a given Chinese question. CLRQR first extracts essential information (both Chinese and English) from the title and description of the input Chinese question, then performs domain-specific translation of the essential Chinese information into English, …

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …

Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu

Research Collection School Of Computing and Information Systems

A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module …

A Utp Semantics For Communicating Processes With Shared Variables And Its Formal Encoding In Pvs, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin

Research Collection School Of Computing and Information Systems

CSP# (communicating sequential programs) is a modelling language designed for specifying concurrent systems by integrating CSP-like compositional operators with sequential programs updating shared variables. In this work, we define an observation-oriented denotational semantics in an open environment for the CSP# language based on the UTP framework. To deal with shared variables, we lift traditional event-based traces into mixed traces which consist of state-event pairs for recording process behaviours. To capture all possible concurrency behaviours between action/channel-based communications and global shared variables, we construct a comprehensive set of rules on merging traces from processes which run in parallel/interleaving. We also define …

Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani

Research Collection School Of Computing and Information Systems

Selecting an item of interest on smartwatches can be tedious and time-consuming as it involves a series of swipe and tap actions. We present PageFlip, a novel method that combines into a single action multiple touch operations such as command invocation and value selection for efficient interaction on smartwatches. PageFlip operates with a page flip gesture that starts by dragging the UI from a corner of the device. We first design PageFlip by examining its key design factors such as corners, drag directions and drag distances. We next compare PageFlip to a functionally equivalent radial menu and a standard swipe …

Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame

Research Collection School Of Computing and Information Systems

Context: Modern internet-based services, ranging from food-delivery to home-caring, leverage the availability of multiple programmable devices to provide handy services tailored to end-user needs. These services are delivered through an ecosystem of device-specific software components and interfaces (e.g., mobile and wearable device applications). Since they often handle private information (e.g., location and health status), their security and privacy requirements are of crucial importance. Defining and analyzing those requirements is a significant challenge due to the multiple types of software components and devices integrated into software ecosystems. Each software component presents peculiarities that often depend on the context and the devices …

Combined Classifier For Cross-Project Defect Prediction: An Extended Empirical Study, Yun Zhang, David Lo, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

To help developers better allocate testing and debugging efforts, many software defect prediction techniques have been proposed in the literature. These techniques can be used to predict classes that are more likely to be buggy based on past history of buggy classes. These techniques work well as long as a sufficient amount of data is available to train a prediction model. However, there is rarely enough training data for new software projects. To deal with this problem, cross-project defect prediction, which transfers a prediction model trained using data from one project to another, has been proposed and is regarded as …

Real World, Large Scale Iot Systems For Community Eldercare: Experiences And Lessons Learned, Alvin Cerdena Valera, Wei Qi Lee, Hwee-Pink Tan, Hwee Xian Tan, Huiguang Liang

Research Collection School Of Computing and Information Systems

The paradigm of aging-in-place - where the elderly live and age in their own homes, independently and safely, with care provided by the community - is compelling, especially in societies that face both shortages in institutionalized eldercare resources, and rapidly-aging populations. When the number of elderly who live alone rises rapidly, support and care from their communities become increasingly critical. Internet-of-Things(IoT) technologies, particularly in-home monitoring solutions, are becoming mature. They can become the fundamental enabler for smart community eldercare. In this chapter, we share our real-world experiencesgleaned from an ongoing large-scale project on IoT-enabled community eldercare. We identify technology-centric challenges …

Vocal Programming For People With Upper-Body Motor Impairments, Lucas Rosenblatt, Patrick Carrington, Kotaro Hara, Jeffrey P. Bigham

Research Collection School Of Computing and Information Systems

Programming heavily relies on entering text using traditional QWERTY keyboards, which poses challenges for people with limited upper-body movement. Developing tools using a publicly available speech recognition API could provide a basis for keyboard free programming. In this paper, we describe our efforts in design, development, and evaluation of a voice-based IDE to support people with limited dexterity.