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The increasing number of computer science students pushes lecturers andtutors of first-year programming courses to their limits to providehigh-quality feedback to the students. Existing systems that handle automatedgrading primarily focus on the automation of test case executions in thecontext of programming assignments. However, they cannot provide customizedfeedback about the students' errors, and hence, cannot replace the help oftutors. While recent research works in the area of automated grading andfeedback generation address this issue by using automated repair techniques, sofar, to the best of our knowledge, there has been no real-world deployment ofsuch techniques. Based on the research advances in recent years, we have builtan intelligent tutoring system that has the capability of providing automatedfeedback and grading. Furthermore, we designed a Software Engineering coursethat guides third-year undergraduate students in incrementally developing sucha system over the coming years. Each year, students will make contributionsthat improve the current implementation, while at the same time, we can deploythe current system for usage by first year students. This paper describes ourteaching concept, the intelligent tutoring system architecture, and ourexperience with the stakeholders. This software engineering project for thestudents has the key advantage that the users of the system are availablein-house (i.e., students, tutors, and lecturers from the first-year programmingcourses). This helps organize requirements engineering sessions and buildsawareness about their contribution to a "to be deployed" software project. Inthis multi-year teaching effort, we have incrementally built a tutoring systemthat can be used in first-year programming courses. Further, it represents aplatform that can integrate the latest research results in APR for education.

Intelligent Tutoring System: Experience of Linking Software Engineering and Programming Teaching