Programming Languages and Compilers Commons^™

A Domain Specific Language For Digital Forensics And Incident Response Analysis, Christopher D. Stelly

University of New Orleans Theses and Dissertations

One of the longstanding conceptual problems in digital forensics is the dichotomy between the need for verifiable and reproducible forensic investigations, and the lack of practical mechanisms to accomplish them. With nearly four decades of professional digital forensic practice, investigator notes are still the primary source of reproducibility information, and much of it is tied to the functions of specific, often proprietary, tools.

The lack of a formal means of specification for digital forensic operations results in three major problems. Specifically, there is a critical lack of:

a) standardized and automated means to scientifically verify accuracy of digital forensic tools; …

Rhetsec_ | Rhetorical Security, Jennifer Mead

Culminating Projects in English

Rhetsec_ examines the rhetorical situation, the rhetorical appeals, and how phishing emails simulate "real" emails in five categories of phishing emails. While the first focus of cybersecurity is security, you must also understand the language of computers to know how to secure them. Phishing is one way to compromise security using computers, and so the computer becomes a tool for malicious language (phishing emails and malware) to be transmitted. Therefore to be concerned with securing computers, then you must also be concerned with language. Language is rhetoric's domain, and the various rhetorical elements which create an identity of the phisher …

Multimodal Mobile Sensing Systems For Physiological And Psychological Assessment, Nguyen Phan Sinh Huynh

Dissertations and Theses Collection (Open Access)

Sensing systems for monitoring physiological and psychological states have been studied extensively in both academic and industry research for different applications across various domains. However, most of the studies have been done in the lab environment with controlled and complicated sensor setup, which is only suitable for serious healthcare applications in which the obtrusiveness and immobility can be compromised in a trade-off for accurate clinical screening or diagnosing. The recent substantial development of mobile devices with embedded miniaturized sensors are now allowing new opportunities to adapt and develop such sensing systems in the mobile context. The ability to sense physiological …

Agile Earth Observation Satellite Scheduling: An Orienteering Problem With Time-Dependent Profits And Travel Times, Guansheng Peng, Reginald Dewil, Cédric Verbeeck, Aldy Gunawan, Lining Xing, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The scheduling problem of an Agile Earth Observation Satellite is to schedule a subset of weighted observation tasks with each a specific “profit” in order to maximize the total collected profit, under its operational constraints. The “time-dependent transition time” and the “time-dependent profit” are two crucial features of this problem. The former relates to the fact that each pair of consecutive tasks requires a transition time to maneuver the look angle of the camera from the previous task to the next task. The latter follows from the fact that a different look angle of an observation leads to a different …

Sieve: Helping Developers Sift Wheat From Chaff Via Cross-Platform Analysis, Agus Sulistya, Gede A. A. P. Prana, David Lo, Christoph Treude

Research Collection School Of Computing and Information Systems

Software developers have benefited from various sources of knowledge such as forums, question-and-answer sites, and social media platforms to help them in various tasks. Extracting software-related knowledge from different platforms involves many challenges. In this paper, we propose an approach to improve the effectiveness of knowledge extraction tasks by performing cross-platform analysis. Our approach is based on transfer representation learning and word embedding, leveraging information extracted from a source platform which contains rich domain-related content. The information extracted is then used to solve tasks in another platform (considered as target platform) with less domain-related content. We first build a word …

Rplidar A2 Accuracy, Ramiro O. Garcia

STAR Program Research Presentations

Traffic is not only a source of frustration but also a leading cause of death for people under 35 years of age. Recent research has focused on how driver assistance technology can be used to mitigate traffic fatalities and create more enjoyable commutes. In addition, self-driving vehicles can reduce fuel consumption the amount by 5% and increases the number of cars on the highway. To achieve this we need to research reliable sensors. This summer I research Rplidar A2 sensor which hopefully will be responsible for recording distance to the preceding car and helping prevent Insider Attacks or Misbehaviors of …

Preference Learning And Similarity Learning Perspectives On Personalized Recommendation, Duy Dung Le

Dissertations and Theses Collection (Open Access)

Personalized recommendation, whose objective is to generate a limited list of items (e.g., products on Amazon, movies on Netflix, or pins on Pinterest, etc.) for each user, has gained extensive attention from both researchers and practitioners in the last decade. The necessity of personalized recommendation is driven by the explosion of available options online, which makes it difficult, if not downright impossible, for each user to investigate every option. Product and service providers rely on recommendation algorithms to identify manageable number of the most likely or preferred options to be presented to each user. Also, due to the limited screen …

Exploiting Approximation, Caching And Specialization To Accelerate Vision Sensing Applications, Nguyen Loc Huynh

Dissertations and Theses Collection (Open Access)

Over the past few years, deep learning has emerged as state-of-the-art solutions for many challenging computer vision tasks such as face recognition, object detection, etc. Despite of its outstanding performance, deep neural networks (DNNs) are computational intensive, which prevent them to be widely adopted on billions of mobile and embedded devices with scarce resources. To address that limitation, we
focus on building systems and optimization algorithms to accelerate those models, making them more computational-efficient.
First, this thesis explores the computational capabilities of different existing processors (or co-processors) on modern mobile devices. It recognizes that by leveraging the mobile Graphics Processing …

A Machine Learning Model For Clustering Securities, Vanessa Torres, Travis Deason, Michael Landrum, Nibhrat Lohria

SMU Data Science Review

In this paper, we evaluate the self-declared industry classifications and industry relationships between companies listed on either the Nasdaq or the New York Stock Exchange (NYSE) markets. Large corporations typically operate in multiple industries simultaneously; however, for investment purposes they are classified as belonging to a single industry. This simple classification obscures the actual industries within which a company operates, and, therefore, the investment risks of that company.
By using Natural Language Processing (NLP) techniques on Security and Exchange Commission (SEC) filings, we obtained self-defined industry classifications per company. Using clustering techniques such as Hierarchical Agglomerative and k-means clustering we …

Successful Shot Locations And Shot Types Used In Ncaa Men’S Division I Basketball, Olivia D. Perrin

All NMU Master's Theses

The primary purpose of the current study was to investigate the effect of court location (distance and angle from basket) and shot types used on shot success in NCAA Men’s DI basketball during the 2017-18 season. A secondary purpose was to further expand the analysis based on two additional factors: player position (guard, forward, or center) and team ranking. All statistical analyses were completed in RStudio and three binomial logistic regression analyses were performed to evaluate factors that influence shot success; one for all two and three point shot attempts, one for only two point attempts, and one for only …

A Survey On Bluetooth 5.0 And Mesh: New Milestones Of Iot, Juenjie Yin, Zheng Yang, Hao Cao, Tongtong Liu, Zimu Zhou, Chenshu Wu

Research Collection School Of Computing and Information Systems

No abstract provided.

Multiagent Decision Making And Learning In Urban Environments, Akshat Kumar

Research Collection School Of Computing and Information Systems

Our increasingly interconnected urban environments provide several opportunities to deploy intelligent agents—from self-driving cars, ships to aerial drones—that promise to radically improve productivity and safety. Achieving coordination among agents in such urban settings presents several algorithmic challenges—ability to scale to thousands of agents, addressing uncertainty, and partial observability in the environment. In addition, accurate domain models need to be learned from data that is often noisy and available only at an aggregate level. In this paper, I will overview some of our recent contributions towards developing planning and reinforcement learning strategies to address several such challenges present in largescale urban …

Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed

Publications and Research

Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages and platforms. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite, e.g., collections, and infinite data structures. However, using this API efficiently involves subtle considerations such as determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. Also, streams may not run all operations in parallel depending on particular collectors used in reductions. In …

Tests As Maintainable Assets Via Auto-Generated Spies: A Case Study Involving The Scala Collections Library's Iterator Trait, Konstantin Läufer, John O'Sullivan, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

In testing stateful abstractions, it is often necessary to record interactions, such as method invocations, and express assertions over these interactions. Following the Test Spy design pattern, we can reify such interactions programmatically through additional mutable state. Alternatively, a mocking framework, such as Mockito, can automatically generate test spies that allow us to record the interactions and express our expectations in a declarative domain-specific language. According to our study of the test code for Scala’s Iterator trait, the latter approach can lead to a significant reduction of test code complexity in terms of metrics such as code size (in some …

Practical And Effective Sandboxing For Linux Containers, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai

Research Collection School Of Computing and Information Systems

A container is a group of processes isolated from other groups via distinct kernel namespaces and resource allocation quota. Attacks against containers often leverage kernel exploits through the system call interface. In this paper, we present an approach that mines sandboxes and enables fine-grained sandbox enforcement for containers. We first explore the behavior of a container by running test cases and monitor the accessed system calls including types and arguments during testing. We then characterize the types and arguments of system call invocations and translate them into sandbox rules for the container. The mined sandbox restricts the container’s access to …

Developing 5gl Concepts From User Interactions, David Stuckless Meyer

Masters Theses

In the fulfilling of the contracts generated in Test Driven Development, a developer could be said to act as a constraint solver, similar to those used by a 5th Generation Language(5GL). This thesis presents the hypothesis that 5GL linguistic mechanics, such as facts, rules and goals, will be emergent in the communications of developer pairs performing Test Driven Development, validating that 5GL syntax is congruent with the ways that practitioners communicate. Along the way, nomenclatures and linguistic patterns may be observed that could inform the design of future 5GL languages.

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

Resource Constrained Deep Reinforcement Learning, Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Computing and Information Systems

In urban environments, resources have to be constantly matched to the “right” locations where customer demand is present. For instance, ambulances have to be matched to base stations regularly so as to reduce response time for emergency incidents in ERS (Emergency Response Systems); vehicles (cars, bikes among others) have to be matched to docking stations to reduce lost demand in shared mobility systems. Such problems are challenging owing to the demand uncertainty, combinatorial action spaces and constraints on allocation of resources (e.g., total resources, minimum and maximum number of resources at locations and regions). Existing systems typically employ myopic and …

On True Language Understanding, Seng-Beng Ho, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Despite the relative successes of natural language processing in providing some useful interfaces for users, natural language understanding is a much more difficult issue. Natural language processing was one of the main topics of AI for as long as computers were put to the task of generating intelligent behavior, and a number of systems that were created since the inception of AI have also been characterized as being capable of natural language understanding. However, in the existing domain of natural language processing and understanding, a definition and consensus of what it means for a system to “truly” understand language do …

Semantic Patches For Java Program Transformation (Artifact), Hong Jin Kang, Thung Ferdian, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo

Research Collection School Of Computing and Information Systems

The program transformation tool Coccinelle is designed for making changes that is required in many locations within a software project. It has been shown to be useful for C code and has been been adopted for use in the Linux kernel by many developers. Over 6000 commits mentioning the use of Coccinelle have been made in the Linux kernel. Our artifact, Coccinelle4J, is an extension to Coccinelle in order for it to apply program transformations to Java source code. This artifact accompanies our experience report “Semantic Patches for Java Program Transformation”, in which we show a case study of applying …

Tests As Maintainable Assets Via Auto-Generated Spies: A Case Study Involving The Scala Collections Library's Iterator Trait, Konstantin Läufer, John O'Sullivan, George K. Thiruvathukal

George K. Thiruvathukal

In testing stateful abstractions, it is often necessary to record interactions, such as method invocations, and express assertions over these interactions. Following the Test Spy design pattern, we can reify such interactions programmatically through additional mutable state. Alternatively, a mocking framework, such as Mockito, can automatically generate test spies that allow us to record the interactions and express our expectations in a declarative domain-specific language. According to our study of the test code for Scala’s Iterator trait, the latter approach can lead to a significant reduction of test code complexity in terms of metrics such as code size (in some …

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 …

Impact Of Http Cookie Violations In Web Archives, Sawood Alam, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

Certain HTTP Cookies on certain sites can be a source of content bias in archival crawls. Accommodating Cookies at crawl time, but not utilizing them at replay time may cause cookie violations, resulting in defaced composite mementos that never existed on the live web. To address these issues, we propose that crawlers store Cookies with short expiration time and archival replay systems account for values in the Vary header along with URIs.

Corrn: Cooperative Reflection Removal Network, Renjie Wen, Boxin Shi, Haoliang Li, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks. Non-learning based methods utilize different handcrafted priors such as the separable sparse gradients caused by different levels of blurs, which often fail due to their limited description capability to the properties of real-world reflections. In this paper, we propose a network with the feature-sharing strategy to tackle this problem in a cooperative and unified framework, by integrating image context information and the multi-scale gradient information. To remove the strong reflections existed in some local regions, we propose a statistic loss by …

Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed

Publications and Research

Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we present an automated refactoring approach that assists developers in writing efficient stream code in a semantics-preserving fashion. The …

3d Canopy Model Reconstruction From Unmanned Aerial System And Automated Single Tree Extraction, Hai Ha Duong

MSU Graduate Theses

This project aims to develop and assess methodology for spatial modeling and extracting individual trees from high spatial resolution Digital Surface Model (DSMs) derived from unmanned aerial system (UAS) or drone-based aerial photos. Those results could be used for monitoring of vegetative response of forests, grasslands and vineyards to regional and localized fluctuations in climate and seasonality. The primary objective of this research is to extract 3D spatial information using drone-based aerial imagery through photogrammetric methods. UAS flights were taken place at phenologically critical times over several locations owned and managed by Missouri State University (MSU). The 3D DSM can …

Declassification Of Faceted Values In Javascript, Shreya Gangishetty

Master's Projects

This research addresses the issues with protecting sensitive information at the language level using information flow control mechanisms (IFC). Most of the IFC mechanisms face the challenge of releasing sensitive information in a restricted or limited manner. This research uses faceted values, an IFC mechanism that has shown promising flexibility for downgrading the confidential information in a secure manner, also called declassification.

In this project, we introduce the concept of first-class labels to simplify the declassification of faceted values. To validate the utility of our approach we show how the combination of faceted values and first-class labels can build various …

Shared-Environment Call-By-Need, George W. Stelle

Computer Science ETDs

Call-by-need semantics formalize the wisdom that work should be done at most once. It frees programmers to focus more on the correctness of their code, and less on the operational details. Because of this property, programmers of lazy functional languages rely heavily on their compiler to both preserve correctness and generate high-performance code for high level abstractions. In this dissertation I present a novel technique for compiling call-by-need semantics by using shared environments to share results of computation. I show how the approach enables a compiler that generates high-performance code, while staying simple enough to lend itself to formal reasoning. …

Examining Augmented Virtuality Impairment Simulation For Mobile App Accessibility Design, Tsu Wei, Kenny (Zhu Shuwei, Kenny) Choo, Rajesh Krishna Balan, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

With mobile apps rapidly permeating all aspects of daily living with use by all segments of the population, it is crucial to support the evaluation of app usability for specific impaired users to improve app accessibility. In this work, we examine the effects of using our augmented virtuality impairment simulation system–Empath-D–to support experienced designer-developers to redesign a mockup of commonly used mobile application for cataract-impaired users, comparing this with existing tools that aid designing for accessibility. We show that the use of augmented virtuality for assessing usability supports enhanced usability challenge identification, finding more defects and doing so more accurately …

Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia

SMU Data Science Review

In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory …