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- Member of: ASU Electronic Theses and Dissertations
Description
Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole life circle of software developing according to Continuous Delivery concepts in a virtualized environment in Vlab platform.
ContributorsDeng, Yuli (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2013
Description
Debugging is a boring, tedious, time consuming but inevitable step of software development and debugging multiple threaded applications with user interactions is even more complicated. Since concurrency and synchronism are normal features in Android mobile applications, the order of thread execution may vary in every run even with the same input. To make things worse, the target erroneous cases may happen just in a few specific runs. Besides, the randomness of user interactions makes the whole debugging procedure more unpredictable. Thus, debugging a multiple threaded application is a tough and challenging task. This thesis introduces a replay mechanism for debugging user interactive multiple threaded Android applications. The approach is based on the 'Lamport Clock' concept, 'Event Driven' implementation and 'Client-Server' architecture. The debugger tool described in this thesis provides a user controlled debugging environment where users or developers are allowed to use modified record application to generate a log file. During the record time, all the necessary events like thread creation, synchronization and user input are recorded. Therefore, based on the information contained in the generated log files, the debugger tool can replay the application off-line since log files provide the deterministic order of execution. In this case, user or developers can replay an application as many times as they need to pinpoint the errors in the applications.
ContributorsLu, He (Author) / Lee, Yann-Hang (Thesis advisor) / Fainekos, Georgios (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2012
Description
The focus of this document is the examination of a new robot simulator developed to aid students in learning robotics programming and provide the ability to test their programs in a simulated world. The simulator, accessed via a website, provides a simulated environment, programming interface, and the ability to control a simulated robot. The simulated environment consists of a user-customizable maze and a robot, which can be controlled manually, via Web service, or by utilizing the Web programming interface. The Web programming interface provides dropdown boxes from which the users may select various options to program their implementations. It is designed to aid new students in the learning of basic skills and thought processes used to program robots. Data was collected and analyzed to determine how effective this system is in helping students learn. This included how quickly students were able to program the algorithms assigned to them and how many lines of code were used to implement them. Students' performance was also monitored to determine how well they were able to use the program and if there were any significant problems. The students also completed surveys to communicate how well the website helped them learn and understand various concepts. The data collected shows that the website was a helpful learning tool for the students and that they were able to use the programming interface quickly and effectively.
ContributorsDrown, Garrett (Author) / Tsai, Wei-Tek (Thesis advisor) / Chen, Yinong (Thesis advisor) / Claveau, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
The Open Services Gateway initiative (OSGi) framework is a standard of module system and service platform that implements a complete and dynamic component model. Currently most of OSGi implementations are implemented by Java, which has similarities of Android language. With the emergence of Android operating system, due to the similarities between Java and Android, the integration of module system and service platform from OSGi to Android system attracts more and more attention. How to make OSGi run in Android is a hot topic, further, how to find a mechanism to enable communication between OSGi and Android system is a more advanced area than simply making OSGi running in Android. This paper, which aimed to fulfill SOA (Service Oriented Architecture) and CBA (Component Based Architecture), proposed a solution on integrating Felix OSGi platform with Android system in order to build up Distributed OSGi framework between mobile phones upon XMPP protocol. And in this paper, it not only successfully makes OSGi run on Android, but also invents a mechanism that makes a seamless collaboration between these two platforms.
ContributorsDong, Xinyi (Author) / Huang, Dijiang (Thesis advisor) / Dasgupta, Partha (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2012
Description
Experience, whether personal or vicarious, plays an influential role in shaping human knowledge. Through these experiences, one develops an understanding of the world, which leads to learning. The process of gaining knowledge in higher education transcends beyond the passive transmission of knowledge from an expert to a novice. Instead, students are encouraged to actively engage in every learning opportunity to achieve mastery in their chosen field. Evaluation of such mastery typically entails using educational assessments that provide objective measures to determine whether the student has mastered what is required of them. With the proliferation of educational technology in the modern classroom, information about students is being collected at an unprecedented rate, covering demographic, performance, and behavioral data. In the absence of analytics expertise, stakeholders may miss out on valuable insights that can guide future instructional interventions, especially in helping students understand their strengths and weaknesses. This dissertation presents Web-Programming Grading Assistant (WebPGA), a homegrown educational technology designed based on various learning sciences principles, which has been used by 6,000+ students. In addition to streamlining and improving the grading process, it encourages students to reflect on their performance. WebPGA integrates learning analytics into educational assessments using students' physical and digital footprints. A series of classroom studies is presented demonstrating the use of learning analytics and assessment data to make students aware of their misconceptions. It aims to develop ways for students to learn from previous mistakes made by themselves or by others. The key findings of this dissertation include the identification of effective strategies of better-performing students, the demonstration of the importance of individualized guidance during the reviewing process, and the likely impact of validating one's understanding of another's experiences. Moreover, the Personalized Recommender of Items to Master and Evaluate (PRIME) framework is introduced. It is a novel and intelligent approach for diagnosing one's domain mastery and providing tailored learning opportunities by allowing students to observe others' mistakes. Thus, this dissertation lays the groundwork for further improvement and inspires better use of available data to improve the quality of educational assessments that will benefit both students and teachers.
ContributorsParedes, Yancy Vance (Author) / Hsiao, I-Han (Thesis advisor) / VanLehn, Kurt (Thesis advisor) / Craig, Scotty D (Committee member) / Bansal, Srividya (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2023
Description
The purpose of the overall project is to create a simulated environment similar to Google map and traffic but simplified for education purposes. Students can choose different traffic patterns and program a car to navigate through the traffic dynamically based on the changing traffic. The environment used in the project is ASU VIPLE (Visual IoT/Robotics Programming Language Environment). It is a visual programming environment for Computer Science education. VIPLE supports a number of devices and platforms, including a traffic simulator developed using Unity game engine. This thesis focuses on creating realistic traffic data for the traffic simulator and implementing dynamic routing algorithm in VIPLE. The traffic data is generated from the recorded real traffic data published at Arizona Maricopa County website. Based on the generated traffic data, VIPLE programs are developed to implement the traffic simulation based on dynamic changing traffic data.
ContributorsZhang, Zhemin (Author) / Chen, Yinong (Thesis advisor) / Wang, Yalin (Thesis advisor) / De Luca, Gennaro (Committee member) / Arizona State University (Publisher)
Created2022
Description
This paper introduces Zenith, a statically typed, functional programming language that compiles to Lua modules. The goal of Zenith is to be used in tandem with Lua, as a secondary language, in which Lua developers can transition potentially unsound programs into Zenith instead. Here developers will be ensured a set of guarantees during compile time, which are provided through Zenith’s language design and type system. This paper formulates the reasoning behind the design choices in Zenith, based on prior work. This paper also provides a basic understanding and intuitions on the Hindley-Milner type system used in Zenith, and the functional programming data types used to encode unsound functions. With these ideas combined, the paper concludes on how Zenith can provide soundness and runtime safety as a language, and how Zenith may be used with Lua to create safe systems.
ContributorsShrestha, Abhash (Author) / De Luca, Gennaro (Thesis advisor) / Bansal, Ajay (Thesis advisor) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2023
Description
There currently exist various challenges in learning cybersecuirty knowledge, along with a shortage of experts in the related areas, while the demand for such talents keeps growing. Unlike other topics related to the computer system such as computer architecture and computer network, cybersecurity is a multidisciplinary topic involving scattered technologies, which yet remains blurry for its future direction. Constructing a knowledge graph (KG) in cybersecurity education is a first step to address the challenges and improve the academic learning efficiency.
With the advancement of big data and Natural Language Processing (NLP) technologies, constructing large KGs and mining concepts, from unstructured text by using learning methodologies, become possible. The NLP-based KG with the semantic similarity between concepts has brought inspiration to different industrial applications, yet far from completeness in the domain expertise, including education in computer science related fields.
In this research work, a KG in cybersecurity area has been constructed using machine-learning-based word embedding (i.e., mapping a word or phrase onto a vector of low dimensions) and hyperlink-based concept mining from the full dataset of words available using the latest Wikipedia dump. The different approaches in corpus training are compared and the performance based on different similarity tasks is evaluated. As a result, the best performance of trained word vectors has been applied, which is obtained by using Skip-Gram model of Word2Vec, to construct the needed KG. In order to improve the efficiency of knowledge learning, a web-based front-end is constructed to visualize the KG, which provides the convenience in browsing related materials and searching for cybersecurity-related concepts and independence relations.
With the advancement of big data and Natural Language Processing (NLP) technologies, constructing large KGs and mining concepts, from unstructured text by using learning methodologies, become possible. The NLP-based KG with the semantic similarity between concepts has brought inspiration to different industrial applications, yet far from completeness in the domain expertise, including education in computer science related fields.
In this research work, a KG in cybersecurity area has been constructed using machine-learning-based word embedding (i.e., mapping a word or phrase onto a vector of low dimensions) and hyperlink-based concept mining from the full dataset of words available using the latest Wikipedia dump. The different approaches in corpus training are compared and the performance based on different similarity tasks is evaluated. As a result, the best performance of trained word vectors has been applied, which is obtained by using Skip-Gram model of Word2Vec, to construct the needed KG. In order to improve the efficiency of knowledge learning, a web-based front-end is constructed to visualize the KG, which provides the convenience in browsing related materials and searching for cybersecurity-related concepts and independence relations.
ContributorsLin, Fanjie (Author) / Huang, Dijiang (Thesis advisor) / Hsiao, I-Han (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2018
Description
With the advent of Massive Open Online Courses (MOOCs) educators have the opportunity to collect data from students and use it to derive insightful information about the students. Specifically, for programming based courses the ability to identify the specific areas or topics that need more attention from the students can be of immense help. But the majority of traditional, non-virtual classes lack the ability to uncover such information that can serve as a feedback to the effectiveness of teaching. In majority of the schools paper exams and assignments provide the only form of assessment to measure the success of the students in achieving the course objectives. The overall grade obtained in paper exams and assignments need not present a complete picture of a student’s strengths and weaknesses. In part, this can be addressed by incorporating research-based technology into the classrooms to obtain real-time updates on students' progress. But introducing technology to provide real-time, class-wide engagement involves a considerable investment both academically and financially. This prevents the adoption of such technology thereby preventing the ideal, technology-enabled classrooms. With increasing class sizes, it is becoming impossible for teachers to keep a persistent track of their students progress and to provide personalized feedback. What if we can we provide technology support without adding more burden to the existing pedagogical approach? How can we enable semantic enrichment of exams that can translate to students' understanding of the topics taught in the class? Can we provide feedback to students that goes beyond only numbers and reveal areas that need their focus. In this research I focus on bringing the capability of conducting insightful analysis to paper exams with a less intrusive learning analytics approach that taps into the generic classrooms with minimum technology introduction. Specifically, the work focuses on automatic indexing of programming exam questions with ontological semantics. The thesis also focuses on designing and evaluating a novel semantic visual analytics suite for in-depth course monitoring. By visualizing the semantic information to illustrate the areas that need a student’s focus and enable teachers to visualize class level progress, the system provides a richer feedback to both sides for improvement.
ContributorsPandhalkudi Govindarajan, Sesha Kumar (Author) / Hsiao, I-Han (Thesis advisor) / Nelson, Brian (Committee member) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2016
Description
Computational thinking, the creative thought process behind algorithmic design and programming, is a crucial introductory skill for both computer scientists and the population in general. In this thesis I perform an investigation into introductory computer science education in the United States and find that computational thinking is not effectively taught at either the high school or the college level. To remedy this, I present a new educational system intended to teach computational thinking called Genost. Genost consists of a software tool and a curriculum based on teaching computational thinking through fundamental programming structures and algorithm design. Genost's software design is informed by a review of eight major computer science educational software systems. Genost's curriculum is informed by a review of major literature on computational thinking. In two educational tests of Genost utilizing both college and high school students, Genost was shown to significantly increase computational thinking ability with a large effect size.
ContributorsWalliman, Garret (Author) / Atkinson, Robert (Thesis advisor) / Chen, Yinong (Thesis advisor) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2015