Thu 21 Jun 2018 16:35 - 17:00 at Grand Ballroom AB - Programming-Student Feedback Chair(s): Dan Grossman

This paper introduces the “Search, Align, and Repair” data-driven program repair framework to automate feedback generation for introductory programming exercises. Distinct from existing techniques, our goal is to develop an efficient, fully automated, and problem-agnostic technique for large or MOOC-scale introductory programming courses. We leverage the large amount of available student submissions in such settings and develop new algorithms for identifying similar programs, aligning correct and incorrect programs, and repairing incorrect programs by finding minimal fixes. We have implemented our technique in the Sarfgen system and evaluated it on thousands of real student attempts from the Microsoft-DEV204.1x edX course and the Microsoft CodeHunt platform. Our results show that Sarfgen can, within two seconds on average, generate concise, useful feedback for 89.7% of the incorrect student submissions. It has been integrated with the Microsoft-DEV204.1X edX class and deployed for production use.

Thu 21 Jun
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16:10 - 17:00: Programming-Student FeedbackPLDI Research Papers at Grand Ballroom AB
Chair(s): Dan GrossmanUniversity of Washington
16:10 - 16:35
Talk
Automated Clustering and Program Repair for Introductory Programming Assignments
PLDI Research Papers
Sumit GulwaniMicrosoft Research, Ivan RadičekVienna University of Technology, Austria, Florian ZulegerTU Vienna
Media Attached
16:35 - 17:00
Talk
Search, Align, and Repair: Data-Driven Feedback Generation for Introductory Programming Exercises
PLDI Research Papers
Ke WangUniversity of California at Davis, USA, Rishabh SinghGoogle Brain, Zhendong SuUniversity of California, Davis
Media Attached