Programming Languages and Compilers Commons^™

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges ...

A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi T. Khatchadourian, Mehdi Bagherzadeh

Publications and Research

Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, a massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log ...

Demonstration Of Cyberattacks And Mitigation Of Vulnerabilities In A Webserver Interface For A Cybersecure Power Router, Benjamin Allen

Computer Science and Computer Engineering Undergraduate Honors Theses

Cyberattacks are a threat to critical infrastructure, which must be secured against them to ensure continued operation. A defense-in-depth approach is necessary to secure all layers of a smart-grid system and contain the impact of any exploited vulnerabilities. In this undergraduate thesis a webserver interface for smart-grid devices communicating over Modbus TCP was developed and exposed to SQL Injection attacks and Cross-Site Scripting attacks. Analysis was performed on Supply-Chain attacks and a mitigation developed for attacks stemming from compromised Content Delivery Networks. All attempted attacks were unable to exploit vulnerabilities in the webserver due to its use of input sanitization ...

A Study Of Software Development Methodologies, Kendra Risener

Computer Science and Computer Engineering Undergraduate Honors Theses

Software development methodologies are often overlooked by software engineers as aspects of development that are handled by project managers alone. However, if every member of the team better understood the development methodology being used, it increases the likelihood that the method is properly implemented and ultimately used to complete the project more efficiently. Thus, this paper seeks to explore six common methodologies: the Waterfall Model, the Spiral Model, Agile, Scrum, Kanban, and Extreme Programming. These are discussed in two main sections in the paper. In the first section, the frameworks are isolated and viewed by themselves. The histories, unique features ...

Side-Channel Analysis On Post-Quantum Cryptography Algorithms, Tristen Teague

Computer Science and Computer Engineering Undergraduate Honors Theses

The advancements of quantum computers brings us closer to the threat of our current asymmetric cryptography algorithms being broken by Shor's Algorithm. NIST proposed a standardization effort in creating a new class of asymmetric cryptography named Post-Quantum Cryptography (PQC). These new algorithms will be resistant against both classical computers and sufficiently powerful quantum computers. Although the new algorithms seem mathematically secure, they can possibly be broken by a class of attacks known as side-channels attacks (SCA). Side-channel attacks involve exploiting the hardware that the algorithm runs on to figure out secret values that could break the security of the ...

Gauging The State-Of-The-Art For Foresight Weight Pruning On Neural Networks, Noah James

Computer Science and Computer Engineering Undergraduate Honors Theses

The state-of-the-art for pruning neural networks is ambiguous due to poor experimental practices in the field. Newly developed approaches rarely compare to each other, and when they do, their comparisons are lackluster or contain errors. In the interest of stabilizing the field of pruning, this paper initiates a dive into reproducing prominent pruning algorithms across several architectures and datasets. As a first step towards this goal, this paper shows results for foresight weight pruning across 6 baseline pruning strategies, 5 modern pruning strategies, random pruning, and one legacy method (Optimal Brain Damage). All strategies are evaluated on 3 different architectures ...

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of ...

Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack

Honors College Theses

Various techniques are used to create predictions based on count data. This type of data takes the form of a non-negative integers such as the number of claims an insurance policy holder may make. These predictions can allow people to prepare for likely outcomes. Thus, it is important to know how accurate the predictions are. Traditional statistical approaches for predicting count data include Poisson regression as well as negative binomial regression. Both methods also have a zero-inflated version that can be used when the data has an overabundance of zeros. Another procedure is to use computer algorithms, also known as ...

Itss: Interactive Web-Based Authoring And Playback Integrated Environment For Programming Tutorials, Eng Lieh Ouh, Benjamin Gan, David Lo

Research Collection School Of Computing and Information Systems

Video-based programming tutorials are a popular form of tutorial used by authors to guide learners to code. Still, the interactivity of these videos is limited primarily to control video flow. There are existing works with increased interactivity that are shown to improve the learning experience. Still, these solutions require setting up a custom recording environment and are not well-integrated with the playback environment. This paper describes our integrated ITSS environment and evaluates the ease of authoring and playback of our interactive programming tutorials. Our environment is designed to run within the browser sandbox and is less intrusive to record interactivity ...

Preprocessing Of Astronomical Images From The Neowise Survey For Near-Earth Asteroid Detection, Rachel Meyer

Scholar Week 2016 - present

Asteroid detection is a common field in astronomy for planetary defense which requires observations from survey telescopes to detect and classify different objects. The amount of data collected each night is increasing as better designed telescopes are created each year. This amount is quickly becoming unmanageable and many researchers are looking for ways to better process this data. The dominant solution is to implement computer algorithms to automatically detect these sources and to use Machine Learning in order to create a more efficient and accurate classifier. In the past there has been a focus on larger asteroids that create streaks ...

Jscsp: A Novel Policy-Based Xss Defense Mechanism For Browsers, Guangquan Xu, Xiaofei Xie, Shuhan Huang, Jun Zhang, Lei Pan, Wei Lou, Kaitai Liang

Research Collection School Of Computing and Information Systems

To mitigate cross-site scripting attacks (XSS), the W3C group recommends web service providers to employ a computer security standard called Content Security Policy (CSP). However, less than 3.7 percent of real-world websites are equipped with CSP according to Google’s survey. The low scalability of CSP is incurred by the difficulty of deployment and non-compatibility for state-of-art browsers. To explore the scalability of CSP, in this article, we propose JavaScript based CSP (JSCSP), which is able to support most of real-world browsers but also to generate security policies automatically. Specifically, JSCSP offers a novel self-defined security policy which enforces ...

The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad

International Journal for Research in Education

Abstract

This study aimed to identify the effect of using the gamification strategy on academic achievement and motivation towards learning problem-solving skills in computer and information technology course. A quasi-experimental method was adopted. The study population included tenth-grade female students in Al-Badi’ah schools in Riyadh. The sample consisted of 54 students divided into two equal groups: control group and experimental group. The study tools comprised an achievement test and the motivation scale. The results showed that there were statistically significant differences between the two groups in the academic achievement test in favor of the experimental group, with a large ...

Taming The Data In The Internet Of Vehicles, Shahab Tayeb

Mineta Transportation Institute Publications

As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to ...

Steps Before Syntax: Helping Novice Programmers Solve Problems Using The Pcdit Framework, Oka Kurniawan, Cyrille Jegourel, Norman Tiong Seng Lee, Matthieu De Mari, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Novice programmers often struggle with problem solving due to the high cognitive loads they face. Furthermore, many introductory programming courses do not explicitly teach it, assuming that problem solving skills are acquired along the way. In this paper, we present 'PCDIT', a non-linear problem solving framework that provides scaffolding to guide novice programmers through the process of transforming a problem specification into an implemented and tested solution for an imperative programming language. A key distinction of PCDIT is its focus on developing concrete cases for the problem early without actually writing test code: students are instead encouraged to think about ...

The Impact Of Programming Language’S Type On Probabilistic Machine Learning Models, Sherif Elsaid

Master's Projects

Software development is an expensive and difficult process. Mistakes can be easily made, and without extensive review process, those mistakes can make it to the production code and may have unintended disastrous consequences.

This is why various automated code review services have arisen in the recent years. From AWS’s CodeGuro and Microsoft’s Code Analysis to more integrated code assistants, like IntelliCode and auto completion tools. All of which are designed to help and assist the developers with their work and help catch overlooked bugs.

Thanks to recent advances in machine learning, these services have grown tremen- dously in ...

Applying Simulated Annealing As An Intelligent Genetic Mutation Operator For Finding Most Probable Explanations On Bayesian Belief Networks, Sahr Attia Afara

Archived Theses and Dissertations

No abstract provided.

Jited: A Framework For Jit Education In The Classroom, Caleb Watts

Master's Theses

The study of programming languages is a rich field within computer science, incorporating both the abstract theoretical portions of computer science and the platform specific details. Topics studied in programming languages, chiefly compilers or interpreters, are permanent fixtures in programming that students will interact with throughout their career. These systems are, however, considerably complicated, as they must cover a wide range of functionality in order to enable languages to be created and run. The process of educating students thus requires that the demanding workload of creating one of the systems be balanced against the time and resources present in a ...

Web Service Quality-Dased Profiling And Selection, Ahmed Magdi Hamza

Archived Theses and Dissertations

Guaranteeing quality of service has been recently labeled as one of multiple major research challenges in the service oriented architecture. In effect, Web service selection from a set of matched services offering the same functional requirements, and ultimately claiming certain quality of service guarantees about themselves is not enough. A need emerges for the existence of a trusted third party that monitors Web service quality indicators, yet in a way that does not interfere with the normal operation of the Web service itself. The third party will eventually provide consumers with guarantees about Web service quality. In this research we ...

The Development Of Qmms: A Case Study For Reliable Online Quiz Maker And Management System, Mohamed Abdelmoneim Elshafey Dr., Tarek Said Ghoniemy Dr.

Future Computing and Informatics Journal

The e-learning and assessment systems became a dominant technology nowadays and distribute across the globe. With severe consequences of COVID19-like crises, the key importance of such technology appeared in which courses, quizzes and questionnaires have to be conducted remotely. Moreover, the use of Learning Management Systems (LMSs), such as blackboard, eCollege, and Moodle, has been sanctioned in all respects of education. This paper presents an open-source interactive Quiz Maker and Management System (QMMS) that suits the research, education (under-grad, grad, or post-grad), and industrial organizations to perform distant quizzes, training and questionnaires with an integration facility with other LMS tools ...

From Community Search To Community Understanding: A Multimodal Community Query Engine, Zhao Li, Pengcheng Zou, Xia Chen, Shichang Hu, Peng Zhang, Yumou Zhou, Bingsheng He, Yuchen Li, Xing Tang

Research Collection School Of Computing and Information Systems

In this demo, we present an online multi-modal community query engine (MQE1 ) on Alibaba’s billion-scale heterogeneous network. MQE has two distinct features in comparison with existing community query engines. Firstly, MQE supports multimodal community search on heterogeneous graphs with keyword and image queries. Secondly, to facilitate community understanding in real business scenarios, MQE generates natural language descriptions for the retrieved community in combination with other useful demographic information. The distinct features of MQE benefit many downstream applications in Alibaba’s e-commerce platform like recommendation. Our experiments confirm the effectiveness and efficiency of MQE on graphs with billions of edges.