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- Creators: Computer Science and Engineering Program
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Description
Dynamic languages like Java enjoy robust and powerful testing tools like JUnit and Cobertura. On the other hand, while there is no shortage of unit testing frameworks for C, the nature of C makes it difficult to make frameworks as powerful as those for other languages. In this paper, we describe ZTest, a testing framework that addresses some of these shortcomings in the C unit testing landscape. We also discuss results of its application to a medium-sized C project.
ContributorsIadicicco, Alexander (Author) / Bazzi, Rida (Thesis director) / Shrivastava, Aviral (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.
ContributorsMarshall, Grant A (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
The face of computing is constantly changing. Wearable computers in the form of glasses or watches are becoming more and more common. These devices have very small screens (measured in millimeters), and users often interact with them through voice input and audio feedback. Weather is one of the most regularly checked app category on smart devices, but weather results on these devices are often limited to raw data, canned responses, or sentence templates with numbers plugged in. The goal for this project was to build a system that could generate weather forecast text, which could then be read to a user through text-to-speech. By using methods in language generation, the system can generate weather forecast text in millions of different ways. This is all computed locally, and it covers every possible weather case. In order to generate natural weather forecast texts, the system retrieved raw weather data from a weather API and created the text through six methods: content determination, document structuring, sentence aggregation, lexical choice, referring expression generation, and text realization. Content determination is the process of deciding on what information to include in a computer generated text. The document structuring phase deals with the order and structure of the information. Sentence aggregation is the merging of similar sentences to improve readability and to reduce redundancy. Lexical choice is the process of putting words to concepts. Referring expression generation is the process of identifying objects, regions, time periods, and locations within a text. Finally text realization involves creating sentences with proper syntax, morphology, and orthography. Through these six stages, a system was developed that could generate unique weather forecast text from raw data accurately and efficiently. It was built for iOS devices with Apple's new programming language, Swift, and it will be ported to the Apple Watch when the API is fully opened to developers.
ContributorsJorgensen, Jacob Paul (Author) / Baral, Chitta (Thesis director) / Faucon, Christophe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
While not officially recognized as an addictive activity by the Diagnostic and Statistical Manual of Mental Disorders, video game addiction has well-documented resources pointing to its effects on physiological and mental health for both addict and those close to the addict. With the rise of eSports, treating video game addiction has become trickier as a passionate and growing fan base begins to act as a culture not unlike traditional sporting. These concerns call for a better understanding of what constitutes a harmful addiction to video games as its heavy practice becomes more financially viable and accepted into mainstream culture.
ContributorsGohil, Abhishek Bhagirathsinh (Author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Investment real estate is unique among similar financial instruments by nature of each property's internal complexities and interaction with the external economy. Where a majority of tradable assets are static goods within a dynamic market, real estate investments are dynamic goods within a dynamic market. Furthermore, investment real estate, particularly commercial properties, not only interacts with the surrounding economy, it reflects it. Alive with tenancy, each and every commercial investment property provides a microeconomic view of businesses that make up the local economy. Management of commercial investment real estate captures this economic snapshot in a unique abundance of untapped statistical data. While analysis of such data is undeniably valuable, the efforts involved with this process are time consuming. Given this unutilized potential our team has develop proprietary software to analyze this data and communicate the results automatically though and easy to use interface. We have worked with a local real estate property management and ownership firm, Reliance Management, to develop this system through the use of their current, historical, and future data. Our team has also built a relationship with the executives of Reliance Management to review functionality and pertinence of the system we have dubbed, Reliance Dashboard.
ContributorsBurton, Daryl (Co-author) / Workman, Jack (Co-author) / LePine, Marcie (Thesis director) / Atkinson, Robert (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Management (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
CourseKarma is a web application that engages students in their own learning through peer-driven social networking. The influence of technology on students is advancing faster than the school system, and a major gap still lingers between traditional learning techniques and the fast-paced, online culture of today's generation. CourseKarma enriches the educational experience of today's student by creating a space for collaborative inquiry as well as illuminating the opportunities of self and group learning through online collaboration. The features of CourseKarma foster this student-driven environment. The main focus is on a news-feed and Question and Answer component that provides a space for students to share instant updates as well ask and answer questions of the community. The community can be as broad as the entire ASU student body, as specific as students in BIO155, or even more targeted via specific subjects and or skills. CourseKarma also provides reputation points, which are the sum of all of their votes received, identifying the individual's level and or ranking in each subject or class. This not only gamifies the usual day-to-day learning environment, but it also provides an in-depth analysis of the individual's skills, accomplishments, and knowledge. The community is also able to input and utilize course and professor descriptions/feedback. This will be in a review format providing the students an opportunity to share and give feedback on their experience as well as providing incoming students the opportunity to be prepared for their future classes. All of the student's contributions and collaborative activity within CourseKarma is displayed on their personal profile creating a timeline of their academic achievements. The application was created using modern web programming technologies such as AngualrJS, Javascript, jQuery, Bootstrap, HTML5, CSS3 for the styling and front-end development, Mustache.js for client side templating, and Firebase AngularFire as the back-end and NoSQL database. Other technologies such as Pivitol Tracker was used for project management and user story generation, as well as, Github for version control management and repository creation. Object-oreinted programming concepts were heavily present in the creation of the various data structures, as well as, a voting algorithm was used to manage voting of specific posts. Down the road, CourseKarma could even be a necessary add-on within LinkedIn or Facebook that provides a quick yet extremely in-depth look at an individuals' education, skills, and potential to learn \u2014 based all on their actual contribution to their academic community rather than just a text they wrote up.
ContributorsCho, Sungjae (Author) / Mayron, Liam (Thesis director) / Lobock, Alan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Arts, Media and Engineering (Contributor)
Created2015-05
Description
The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques to align natural language sentences to the linearized parses of their associated knowledge representations in order to learn the meanings of individual words. The work includes proposing and analyzing an approach that can be used to learn some of the initial lexicon.
ContributorsBaldwin, Amy Lynn (Author) / Baral, Chitta (Thesis director) / Vo, Nguyen (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The modern web presents an opportunity for educators and researchers to create tools that are highly accessible. Because of the near-ubiquity of modern web browsers, developers who hope to create educational and analytical tools can reach a large au- dience by creating web applications. Using JavaScript, HTML, and other modern web development technologies, Genie was developed as a simulator to help educators in biology, genetics, and evolution classrooms teach their students about population genetics. Because Genie was designed for the modern web, it is highly accessible to both educators and students, who can access the web application using any modern web browser on virtually any device. Genie demonstrates the efficacy of web devel- opment technologies for demonstrating and simulating complex processes, and it will be a unique educational tool for educators who teach population genetics.
ContributorsRoos, Benjamin Hirsch (Author) / Cartwright, Reed (Thesis director) / Wilson Sayres, Melissa (Committee member) / Mayron, Liam (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The purpose of this project was to program a Raspberry Pi to be able to play music from both local storage on the Pi and from internet radio stations such as Pandora. The Pi also needs to be able to play various types of file formats, such as mp3 and FLAC. Finally, the project is also to be driven by a mobile app running on a smartphone or tablet. To achieve this, a client server design was employed where the Raspberry Pi acts as the server and the mobile app is the client. The server functionality was achieved using a Python script that listens on a socket and calls various executables that handle the different formats of music being played. The client functionality was achieved by programming an Android app in Java that sends encoded commands to the server, which the server decodes and begins playing the music that command dictates. The designs for both the client and server are easily extensible and allow for any future modifications to the project to be easily made.
ContributorsStorto, Michael Olson (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
With the development of technology, there has been a dramatic increase in the number of machine learning programs. These complex programs make conclusions and can predict or perform actions based off of models from previous runs or input information. However, such programs require the storing of a very large amount of data. Queries allow users to extract only the information that helps for their investigation. The purpose of this thesis was to create a system with two important components, querying and visualization. Metadata was stored in Sedna as XML and time series data was stored in OpenTSDB as JSON. In order to connect the two databases, the time series ID was stored as a metric in the XML metadata. Queries should be simple, flexible, and return all data that fits the query parameters. The query language used was an extension of XQuery FLWOR that added time series parameters. Visualization should be easily understood and be organized in a way to easily find important information and details. Because of the possibility of a large amount of data being returned from a query, a multivariate heat map was used to visualize the time series results. The two programs that the system performed queries on was Energy Plus and Epidemic Simulation Data Management System. By creating such a system, it would be easier for people of the project's fields to find the relationship between metadata that leads to the desired results over time. Over the time of the thesis project, the overall software was completed, however the software must be optimized in order to take the enormous amount of data expected from the system.
ContributorsTse, Adam Yusof (Author) / Candan, Selcuk (Thesis director) / Chen, Xilun (Committee member) / Barrett, The Honors College (Contributor) / School of Music (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05