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A Workflow for Practical Programming Class Management Using GitHub Pages and GitHub Classroom

  • Aaron Daniel Snowberger;Choong Ho Lee
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.331-339
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    • 2023
  • In programming classes, there is always a need to efficiently manage programming assignments. This is especially important as class sizes and assignment complexity grows. GitHub and GitHub Classroom makes the management of student assignments much simpler than uploading files and folders to a LMS or shared online drive. Additionally, git and GitHub are industry standard tools, so introducing students these tools in class provides them a good opportunity to start learning about how software is developed in the real-world. This study describes a workflow that uses both GitHub Pages and GitHub Classroom for more efficient classroom and assignment management. The workflow outlined in this study was used in two practical web programming classes in Spring 2023 with 46 third and fourth-year university students. GitHub Pages was used as a classroom website to distribute class announcements, assignments, lecture slides, study guides, and exams. GitHub Classroom was used as a class roster and assignment management platform. The workflow presented in this study is expected to assist other lecturers with the formidable tasks of distributing, collecting, grading, and leaving feedback on multiple students' multi-file programming assignments in practical programming classes.

Creating a Standardized Environment for Efficient Learning Management using GitHub Codespaces and GitHub Classroom

  • Aaron Daniel Snowberger;Kangsoo You
    • Journal of Practical Engineering Education
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    • v.16 no.3_spc
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    • pp.267-274
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    • 2024
  • One challenge with teaching practical programming classes is the standardization of development tools on student computers. This is particularly true when a complicated setup process is required before beginning to code, or in remote classes, such as those necessitated by the COVID-19 pandemic, where the instructor cannot provide individual troubleshooting assistance. In such cases, students who encounter problems during the setup process may give up on the class altogether before even beginning to code. Therefore, this paper recommends using GitHub Codespaces as a tool for implementing standardized student development environments from day one. Codespaces provides Docker containers that an instructor can configure in such a way as to enable students to practice installing various coding tools within a controlled space, while also providing a language-specific, fully optimized development environment. In addition, Codespaces may be used more effectively in collaboration with GitHub Classroom, which helps instructors manage both the starter code and coding environment in which students work. In this paper, we compare two semesters of university Node.JS programming classes that utilized different development environments: one localized on student computers, the other containerized in Codespaces online. Then, we discuss how GitHub Codespaces and GitHub Classroom can be used to increase the effectiveness of practical programming classes while also increasing student engagement and programming confidence in class.

A Study of GitHub Documentation Repositories: What Makes GitHub Documentation Repository Popular? (깃허브 문서 저장소들에 대한 연구: 무엇이 깃허브 문서 저장소를 유명하게 하는가?)

  • Jung Il Kim
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.8
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    • pp.374-381
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    • 2024
  • Documentation repositories on GitHub are used to share information that is helpful in performing various tasks. Popular documentation repositories have an advantage in attracting contributors who can help manage and extend documentation repository. Therefore, it is important to understand the characteristic of documentation repositories helpful to obtain popularity for developing strategies attracting attention of users. This paper presents a study on GitHub documentation repositories. To conduct the study, we collected 566 documentation repositories from GitHub and manually categorized their topic into 30 topics. Based on the stargazer score of the collected documentation repositories, we divided the collected documentation repositories into popular and unpopular documentation repository groups and investigated the topics in the popular documentation group. Then we statistically examined the differences in README characteristics of the popular and unpopular documentation repository groups. As a result, we found that the studied documentation repositories have 23 popular topics. We also found that the popular and unpopular documentation repository groups have differences in 5 README characteristics. The result of our study indicates that what documentation repository become popular in GitHub.

Anglicisms in the Field of Information Technology: Analysis of Linguistic Features

  • Antonina, Plechko;Tetiana, Chukhno;Tetiana, Nikolaieva;Liliia, Apolonova;Tetiana, Leleka
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.183-192
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    • 2022
  • The role that English currently plays is undeniable. It has become the most common means of communication among native speakers of several languages around the world. English penetrates into all areas of people's daily lives. In the field of Information Technology (IT), English has taken a dominant position, as many of the terms used on a daily basis are written in English. The purpose of the article is to analyze the linguistic features of anglicisms in the field of Information Technology. Methods. The research is based on systematic and comparative analysis, dialectical method, as well as methods of classification and generalization. Results. This study presents the results of compiling a multilingual glossary with anglicisms used in the GitHub and 3D Slicer fields. Despite the limited number of terms included in the glossary, the article provides a lot of evidence for the influence of the English language in the areas of Information Technology, GitHub and 3D Slicer under consideration. The types of anglicisms used in the 3D Slicer area seem to be more diverse than in the GitHub area. This study found that five European languages use language strategies to solve any communication problem. The multilingual glossary showed that in some cases there is a coexistence between Anglicism and the native term. In other cases, the English term is the only one used in different languages. There are cases when only the native language is used. Conclusions. This study is a useful tool that helps to improve the efficiency of communication between engineers and technicians who speak different native languages. The ultimate goal of this research will be to create a multilingual glossary that is still under development and is likely to cover other IT areas such as Python and VTK.

Identifying the Network Characteristics of Contributors That Affect Performance in Open Collaboration : Focusing on the GitHub Open Source (개방형협업 참여자 기여도와 네트워크 특성과의 관계에 대한 연구 : 깃허브 오픈소스 프로젝트를 중심으로)

  • Baek, Hyunmi;Oh, Sehwan
    • The Journal of Society for e-Business Studies
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    • v.20 no.1
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    • pp.23-43
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    • 2015
  • Information and communications technology facilitates collaboration among individuals by functioning as an open platform for open collaboration projects. In this regard, this study aims to understand the network characteristics of participants who contribute greatly to open collaboration by investigating the mutual cooperation network in an open source project, which represents a form of open collaboration based on social network theory. To achieve this objective, this study analyzes the network centrality of developers with a high number of commits, particularly 8,101 developers in 782 repositories in GitHub, a representative open source platform. This study also determines how the relationship between network centrality and number of commits depends on the size of a repository network and the presence of a hub. Consequently, the number of commits by developers with high degree, betweenness, and closeness centrality is increasing. Among which, betweenness centrality has the highest explanatory power. Furthermore, when a hub is present and as network size increases, the relationship between the betweenness centrality of a developer and his/her number of commits continues to grow. This study is expected to provide suggestions for the successful performance of open collaboration projects in the future.

Detecting Meltdown and Spectre Malware through Binary Pattern Analysis (바이너리 패턴 분석을 이용한 멜트다운, 스펙터 악성코드 탐지 방법)

  • Kim, Moon-sun;Lee, Man-hee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.6
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    • pp.1365-1373
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    • 2019
  • Meltdown and Spectre are vulnerabilities that exploit out-of-order execution and speculative execution techniques to read memory regions that are not accessible with user privileges. OS patches were released to prevent this attack, but older systems without appropriate patches are still vulnerable. Currently, there are some research to detect Meltdown and Spectre attacks, but most of them proposed dynamic analysis methods. Therefore, this paper proposes a binary signature that can be used to detect Meltdown and Spectre malware without executing them. For this, we collected 13 malicious codes from GitHub and performed binary pattern analysis. Based on this, we proposed a static detection method for Meltdown and Spectre malware. Our results showed that the method identified all the 19 attack files with 0.94% false positive rate when applied to 2,317 normal files.

Development of a Python-based Algorithm for Image Analysis of Outer-ring Galaxies (외부고리 은하 영상 분석을 위한 파이썬 기반 알고리즘 개발)

  • Jo, Hoon;Sohn, Jungjoo
    • Journal of the Korean earth science society
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    • v.43 no.5
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    • pp.579-590
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    • 2022
  • In this study, we aimed to develop a Python-based outer-ring galaxy analysis algorithm according to the data science process. We assumed that the potential users are citizen scientists, including students and teachers. In the actual classification studies using real data of galaxies, a specialized software called IRAF is used, thereby limiting the general public's access to the software. Therefore, an image analysis algorithm was developed for the outer-ring galaxies as targets, which were compared with those of the previous research. The results of this study were compared with those of studies conducted using IRAF to verify the performance of the newly developed image analysis algorithm. Among the 69 outer-ring galaxies in the first test, 50 cases (72.5%) showed high agreement with the previous research. The remaining 19 cases (27.5%) showed differences that were caused by the presence of bright stars overlapped in the line of sight or weak brightness in the inner galaxy. To increase the usability of the finished product that has undergone a supplementary process, all used data, algorithms, Python code files, and user manuals were loaded in GitHub and made available as shared educational materials.

Clip Toaster : Pastejacking Attack Detection and Response Technique (클립 토스터 : 페이스트재킹 공격 탐지 및 대응 기술)

  • Lee, Eun-young;Kil, Ye-Seul;Lee, Il-Gu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.192-194
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    • 2022
  • This paper analyzes the attack method of pastejacking and proposes a clip toaster that can effectively defend it. When programming, developers often copy and paste code from GitHub, Stack Overflow, or blogs. Pastejacking is an attack that injects malicious data into the clipboard when a user copies code posted on the web, resulting in security threats by executing malicious commands that the user does not intend or by inserting dangerous code snippets into the software. In this paper, we propose clip toaster to visualize and alertusers of threats to defend pastejacking that threatens the security of the developer's terminal and program code. Clip Toaster can visualize security threat notifications and effectively detect and respond to attacks without interfering with user actions.

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Python Package Production for Agricultural Researcher to Use Meteorological Data (농업연구자의 기상자료 활용을 위한 파이썬 패키지 제작)

  • Hyeon Ji Yang;Joo Hyun Park;Mun-Il Ahn;Min Gu Kang;Yong Kyu Han;Eun Woo Park
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.2
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    • pp.99-107
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    • 2023
  • Recently, the abnormal weather events and crop damages occurred frequently likely due to climate change. The importance of meteorological data in agricultural research is increasing. Researchers can download weather observation data by accessing the websites provided by the KMA (Korea Meteorological Administration) and the RDA (Rural Development Administration). However, there is a disadvantage that multiple inquiry work is required when a large amount of meteorological data needs to be received. It is inefficient for each researcher to store and manage the data needed for research on an independent local computer in order to avoid this work. In addition, even if all the data were downloaded, additional work is required to find and open several files for research. In this study, data collected by the KMA and RDA were uploaded to GitHub, a remote storage service, and a package was created that allows easy access to weather data using Python. Through this, we propose a method to increase the accessibility and usability of meteorological data for agricultural personnel by adopting a method that allows anyone to take data without an additional authentication process.

COVID-19: Improving the accuracy using data augmentation and pre-trained DCNN Models

  • Saif Hassan;Abdul Ghafoor;Zahid Hussain Khand;Zafar Ali;Ghulam Mujtaba;Sajid Khan
    • International Journal of Computer Science & Network Security
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    • v.24 no.7
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    • pp.170-176
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    • 2024
  • Since the World Health Organization (WHO) has declared COVID-19 as pandemic, many researchers have started working on developing vaccine and developing AI systems to detect COVID-19 patient using Chest X-ray images. The purpose of this work is to improve the performance of pre-trained Deep convolution neural nets (DCNNs) on Chest X-ray images dataset specially COVID-19 which is developed by collecting from different sources such as GitHub, Kaggle. To improve the performance of Deep CNNs, data augmentation is used in this study. The COVID-19 dataset collected from GitHub was containing 257 images while the other two classes normal and pneumonia were having more than 500 images each class. There were two issues whike training DCNN model on this dataset, one is unbalanced and second is the data is very less. In order to handle these both issues, we performed data augmentation such as rotation, flipping to increase and balance the dataset. After data augmentation each class contains 510 images. Results show that augmentation on Chest X-ray images helps in improving accuracy. The accuracy before and after augmentation produced by our proposed architecture is 96.8% and 98.4% respectively.