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

2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)(2022)

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摘要
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 I NT Tu ToR . Briefly, I NT T UTOR 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 I NT T UTOR improves their ability to identify and fix potential bugs or vulnerabilities in the cryptography-related programming assignments.
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关键词
Intelligent Tutoring System,API Misuses,Feedback Generation
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