An Intelligent Tutoring System for API Misuse Correction by Instant Quality Feedback

Rui Zhao, Harvey P. Siy, Chulwoo Pack, Leen-Kiat Soh, Myoungkyu Song
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Abstract

Computer science students have difficulty understanding correct usages of an Application Programming Interface (API) and programming violations that cause compilation or runtime errors. Despite high-quality documentation for programming, the students typically need an instructor's feedback when their programs cause bugs, crashes, and vulnerabilities. This paper presents a pedagogical approach that is based on an Intelligent Tutoring System called INTTuToR. Briefly, INTTUTOR provides novice students with instant feedback to fix their programming issues or vulnerabilities. We have implemented our approach as a plug-in application in the Integrated Development Environment (IDE) for an interactive educational environment. In our proposed evaluation, we plan to perform empirical studies with CS students to assess how effectively INTTUTOR improves their ability to identify and fix potential bugs or vulnerabilities in the cryptography-related programming assignments.
基于即时质量反馈的API误用纠正智能辅导系统
计算机科学专业的学生很难理解应用程序编程接口(API)的正确用法以及导致编译或运行时错误的编程违规。尽管有高质量的编程文档,但当学生的程序导致错误、崩溃和漏洞时,他们通常需要教师的反馈。本文提出了一种基于智能辅导系统INTTuToR的教学方法。简而言之,INTTUTOR为新手提供即时反馈,以修复他们的编程问题或漏洞。我们已经将我们的方法实现为交互式教育环境的集成开发环境(IDE)中的插件应用程序。在我们提出的评估中,我们计划对CS学生进行实证研究,以评估INTTUTOR如何有效地提高他们识别和修复密码学相关编程作业中潜在错误或漏洞的能力。
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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