Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Providing feedback on programming assignments is a tedious task for the instructor, and even impossible in large MOOCs with thousands of students. ,  present a novel technique for automatic feedback generation: (1) For a given programming assignment,  automatically cluster the correct student attempts using a dynamic program analysis. From each cluster  select one student attempt as a specification. (2) Given an incorrect student attempt  run a repair procedure against all specifications, and automatically generate the minimal repair based on one of them.  evaluated the approach on 56,807 student attempts over 18 problems from an undergraduate programming course and a MOOC course. In our evaluation  first automatically clustered the correct student attempts and generated specifications, and then used these specifications to repair the incorrect student attempts without any human intervention, finding repairs for 90% of the incorrect attempts.
['Sumit Gulwani', 'Ivan Radiček', 'Florian Zuleger']
I am writing a research paper on a idea Automated Clustering and Program Repair for Introductory Programming Assignments
[{"from": "human", "value": "I am writing a research paper on a idea Automated Clustering and Program Repair for Introductory Programming Assignments"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Providing feedback on programming assignments is a tedious task for the instructor, and even impossible in large MOOCs with thousands of students. ,  present a novel technique for automatic feedback generation: (1) For a given programming assignment,  automatically cluster the correct student attempts using a dynamic program analysis. From each cluster  select one student attempt as a specification. (2) Given an incorrect student attempt  run a repair procedure against all specifications, and automatically generate the minimal repair based on one of them.  evaluated the approach on 56,807 student attempts over 18 problems from an undergraduate programming course and a MOOC course. In our evaluation  first automatically clustered the correct student attempts and generated specifications, and then used these specifications to repair the incorrect student attempts without any human intervention, finding repairs for 90% of the incorrect attempts."}]