MI-OPJ:一种基于微服务的在线编程判断器

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Big Data Pub Date : 2021-12-15 DOI:10.1109/BigData52589.2021.9671978

Orestis Rafail Nerantzis, Apostolos Tselios, Alexandros Karakasidis

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引用次数: 0

摘要

过去几年我们正在经历的SARS-CoV-2大流行导致我们的许多日常生活活动从现实世界转向数字世界。教育就是一个典型的例子，导师和学生在沟通上都有困难和延迟。为了帮助实现这一方向，同时考虑到在线教育已经形成的未来，我们提出了MI-OPJ，一个基于微服务的在线编程裁判。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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MI-OPJ: A Microservices-based Online Programming Judge

The SARS-CoV-2 pandemic we are experiencing the last few years has resulted in a shift of many of our everyday life activities from the physical to the digital world. Education is a typical example of such a case with both tutors and students experiencing difficulties and delays in communication. To assist towards this direction, also considering the already forming future of online education, we present MI-OPJ, a microservices-based online programming judge.

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.