Physical Sciences and Mathematics Commons^™

Leveraging Defects Life-Cycle For Labeling Defective Classes, Bailey R. Vandehei

Master's Theses

Data from software repositories are a very useful asset to building dierent kinds of

models and recommender systems aimed to support software developers. Specically,

the identication of likely defect-prone les (i.e., classes in Object-Oriented systems)

helps in prioritizing, testing, and analysis activities. This work focuses on automated

methods for labeling a class in a version as defective or not. The most used methods

for automated class labeling belong to the SZZ family and fail in various circum-

stances. Thus, recent studies suggest the use of aect version (AV) as provided by

developers and available in the issue tracker such as …

Predictors Of Ransomware From Binary Analysis, Aaron M. Otis

Master's Theses

Ransomware, a type of malware that extorts payment from a victim by encrypting her data, is a growing threat that is becoming more sophisticated with each generation. Attackers have shifted from targeting individuals to entire organizations, raising extortions from hundreds of dollars to hundreds of thousands of dollars. In this work, we analyze a variety of ransomware and benign software binaries in order to identify indicators that may be used to detect ransomware. We find that several combinations of strings, cryptographic constants, and a large number loops are key indicators useful for detecting ransomware.

Krylov Subspace Spectral Methods With Non-Homogenous Boundary Conditions, Abbie Hendley

Master's Theses

For this thesis, Krylov Subspace Spectral (KSS) methods, developed by Dr. James Lambers, will be used to solve a one-dimensional, heat equation with non-homogenous boundary conditions. While current methods such as Finite Difference are able to carry out these computations efficiently, their accuracy and scalability can be improved. We will solve the heat equation in one-dimension with two cases to observe the behaviors of the errors using KSS methods. The first case will implement KSS methods with trigonometric initial conditions, then another case where the initial conditions are polynomial functions. We will also look at both the time-independent and time-dependent …

Data-Driven Database Education: A Quantitative Study Of Sql Learning In An Introductory Database Course, Andrew C. Von Dollen

Master's Theses

The Structured Query Language (SQL) is widely used and challenging to master. Within the context of lab exercises in an introductory database course, this thesis analyzes the student learning process and seeks to answer the question: ``Which SQL concepts, or concept combinations, trouble students the most?'' We provide comprehensive taxonomies of SQL concepts and errors, identify common areas of student misunderstanding, and investigate the student problem-solving process. We present an interactive web application used by students to complete SQL lab exercises. In addition, we analyze data collected by this application and we offer suggestions for improvement to database lab activities.

Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm

Master's Theses

Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest …

The Performance Cost Of Security, Lucy R. Bowen

Master's Theses

Historically, performance has been the most important feature when optimizing computer hardware. Modern processors are so highly optimized that every cycle of computation time matters. However, this practice of optimizing for performance at all costs has been called into question by new microarchitectural attacks, e.g. Meltdown and Spectre. Microarchitectural attacks exploit the effects of microarchitectural components or optimizations in order to leak data to an attacker. These attacks have caused processor manufacturers to introduce performance impacting mitigations in both software and silicon.

To investigate the performance impact of the various mitigations, a test suite of forty-seven different tests was created. …

Simulating Epidemics And Interventions On High Resolution Social Networks, Christopher E. Siu

Master's Theses

Mathematical models of disease spreading are a key factor of ensuring that we are prepared to deal with the next epidemic. They allow us to predict how an infection will spread throughout a population, thereby allowing us to make intelligent choices when attempting to contain the disease. Whether due to a lack of empirical data, a lack of computational power, a lack of biological understanding, or some combination thereof, traditional models must make sweeping assumptions about the behavior of a population during an epidemic.

In this thesis, we implement granular epidemic simulations using a rich social network constructed from real-world …

Brain Tumor Classification Using Hit-Or-Miss Capsule Layers, Spencer J. Chang

Master's Theses

The job of classifying or annotating brain tumors from MRI images can be time-consuming and difficult, even for radiologists. To increase the survival chances of a patient, medical practitioners desire a means for quick and accurate diagnosis. While datasets like CIFAR, ImageNet, and SVHN have tens of thousands, hundreds of thousands, or millions of samples, an MRI dataset may not have the same luxury of receiving accurate labels for each image containing a tumor. This work covers three models that classify brain tumors using a combination of convolutional neural networks and of the concept of capsule layers. Each network utilizes …

Design And Analysis Of An Instrumenting Profiler For Webassembly, Chandler Gifford

Master's Theses

This thesis presents the design, implementation, and analysis of WasmProf, an instrumenting profiler for WebAssembly programs. WebAssembly is a compiled language designed for use on the web that, at the time of this writing, is still being actively developed. At present, performance analysis for WebAssembly programs mostly consists of browsers’ built-in sampling profilers. These profilers work well in many cases but only give a statistical estimation of the distribution of function calls and are, therefore, not well-suited for more fine-grained analysis. The WasmProf instrumenting profiler fills this analysis gap. WasmProf is capable of tracking the number of calls made and …

Evaluating Projections And Developing Projection Models For Daily Fantasy Basketball, Eric C. Evangelista

Master's Theses

Daily fantasy sports (DFS) has grown in popularity with millions of participants throughout the world. However, studies have shown that most profits from DFS contests are won by only a small percentage of players. This thesis addresses the challenges faced by DFS participants by evaluating sources that provide player projections for NBA DFS contests and by developing machine learning models that produce competitive player projections.

External sources are evaluated by constructing daily lineups based on the projections offered and evaluating those lineups in the context of all potential lineups, as well as those submitted by participants in competitive FanDuel DFS …

Snoring: A Noise Defect Prediction Datasets, Aalok Ahluwalia

Master's Theses

Defect prediction aims at identifying software artifacts that are likely to exhibit a defect. The main purpose of defect prediction is to reduce the cost of testing and code review, by letting developers focus on specific artifacts. Several researchers have worked on improving the accuracy of defect estimation models using techniques such as tuning, re-balancing, or feature selection. Ultimately, the reliability of a prediction model depends on the quality of the dataset. Therefore effort has been spent in identifying sources of noise in the datasets, and how to deal with them, including defect misclassification and defect origin. A key component …

A Machine Learning Technology For Rapid Detection Of Carbon Nanotubes/Dna Hybridization In Biosensor Healthcare Applications, Steven K. Ang

Master's Theses

In molecular biology, the term “DNA hybridization” generally refers to the process of forming a double stranded nucleic acid from joining two complementary strands of DNA. The degree of genetic similarity of the DNA resulting from hybridization can be detected ei ther by using the chemical characteristics of DNA samples or by utilizing reliable biosensors which transform the chemical characteristics into a source of electrical measurements. In past research about such sensors, known as DNA Hybridization Detection Systems, the thermal and electrical characteristics of carbon nanotubes are utilized to detect whether hybridization takes place or not. However, human interpretation of …

Gogo: An Improved Algorithm To Measure The Semantic Similarity Between Gene Ontology Terms, Chenguang Zhao

Master's Theses

Measuring the semantic similarity between Gene Ontology (GO) terms is an essential step in functional bioinformatics research. We implemented a software named GOGO for calculating the semantic similarity between GO terms. GOGO has the advantages of both information-content-based and hybrid methods, such as Resnik’s and Wang’s methods. Moreover, GOGO is relatively fast and does not need to calculate information content (IC) from a large gene annotation corpus but still has the advantage of using IC. This is achieved by considering the number of children nodes in the GO directed acyclic graphs when calculating the semantic contribution of an ancestor node …

Dynamic Shifting Of Virtual Network Topologies For Network Attack Prevention, Lenoy Avidan

Master's Theses

Computer networks were not designed with security in mind, making research into the subject of network security vital. Virtual Networks are similar to computer networks, except the components of a Virtual Network are in software rather than hardware. With the constant threat of attacks on networks, security is always a big concern, and Virtual Networks are no different. Virtual Networks have many potential attack vectors similar to physical networks, making research into Virtual Network security of great importance. Virtual Networks, since they are composed of virtualized network components, have the ability to dynamically change topologies. In this paper, we explore …

A Study Of Face Embedding In Face Recognition, Khanh Duc Le

Master's Theses

Face Recognition has been a long-standing topic in computer vision and pattern recognition field because of its wide and important applications in our daily lives such as surveillance system, access control, and so on. The current modern face recognition model, which keeps only a couple of images per person in the database, can now recognize a face with high accuracy. Moreover, the model does not need to be retrained every time a new person is added to the database.

By using the face dataset from Digital Democracy, the thesis will explore the capability of this model by comparing it with …

Supported Programming For Beginning Developers, Andrew Gilbert

Master's Theses

Testing code is important, but writing test cases can be time consuming, particularly for beginning programmers who are already struggling to write an implementation. We present TestBuilder, a system for test case generation which uses an SMT solver to generate inputs to reach specified lines in a function, and asks the user what the expected outputs would be for those inputs. The resulting test cases check the correctness of the output, rather than merely ensuring the code does not crash. Further, by querying the user for expectations, TestBuilder encourages the programmer to think about what their code ought to do, …

Real-Time Ray Traced Global Illumination Using Fast Sphere Intersection Approximation For Dynamic Objects, Reed Phillip Garmsen

Master's Theses

Realistic lighting models are an important component of modern computer generated, interactive 3D applications. One of the more difficult to emulate aspects of real-world lighting is the concept of indirect lighting, often referred to as global illumination in computer graphics. Balancing speed and accuracy requires carefully considered trade-offs to achieve plausible results and acceptable framerates.

We present a novel technique of supporting global illumination within the constraints of the new DirectX Raytracing (DXR) API used with DirectX 12. By pre-computing spherical textures to approximate the diffuse color of dynamic objects, we build a smaller set of approximate geometry used for …

Dish: Democracy In State Houses, Nicholas A. Russo

Master's Theses

In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we …

Using Software-Defined Networking And Openflow Switching To Reroute Network Traffic Dynamically Based On Traffic Volume Measurements, Ihab Al Shaikhli

Master's Theses

Traditional switching and routing have been very effective for network packet delivery but does create some constraints. for example, all packets from a given source to a given destination must always take the same path. Within a traditional Ethernet network, a tree topology must be used. Software-Defined Networking (SDN) has the potential to bypass this tree-topology limitation by placing the control of the switches and their forwarding tables under a central device called a controller. SDN also allows for sets of controllers. the controller can identify individual network flows and issue commands to the switches to, in effect, assign individual …

Opioid Misuse Detection In Hospitalized Patients Using Convolutional Neural Networks, Brihat Sharma

Master's Theses

Opioid misuse is a major public health problem in the world. In 2016, 11.3 million people were reported to misuse opioids in the US only. Opioid-related inpatient and emergency department visits have increased by 64 percent and the rate of opioid-related visits has nearly doubled between 2009 and 2014. It is thus critical for healthcare systems to detect opioid misuse cases. Patients hospitalized for consequences of their opioid misuse present an opportunity for intervention but better screening and surveillance methods are needed to guide providers. The current screening methods with self-report questionnaire data are time-consuming and difficult to perform in …

Polyxpress+: Using Social Networking To Enhance The User Experience Of An Interactive Location-Based Storytelling Application, Desiree Creel

Master's Theses

There’s no denying the ever increasing presence of social networking in our daily lives. Every day, people share what they are thinking, doing, and experiencing. But even more so, they check their favorite networks to see what the people in their lives are sharing. Social networking has become so prevalent that most applications incorporate it since it keeps users engaged and beckons them back to the application again and again.

PolyXpress is an interactive, location-based storytelling mobile application that functions as a platform for creating and experiencing stories. Written as a research project at California Polytechnic State University, it allows …