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Cited by 17

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Search, align, and repair: data-driven feedback generation for introductory programming exercises

Wang, Ke, Singh, Rishabh, Su, Zhendong·2018·ACM SIGPLAN Notices
DOI 10.1145/3296979.3192384
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Abstract

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.

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Citations

Cites

Show all 27 references

Research works printed but not linked: 4

  1. Alex Groce , Sagar Chaki , Daniel Kroening , and Ofer Strichman . 2006. Error explanation with distance metrics. Tools and Algorithms for the Construction and Analysis of Systems: 10th International Conference , TACAS 2004 , Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2004, Barcelona, Spain, March 29 - April 2, 2004. Proceedings 8, 3 (2006), 229–247. Alex Groce, Sagar Chaki, Daniel Kroening, and Ofer Strichman. 2006. Error explanation with distance metrics. Tools and Algorithms for the Construction and Analysis of Systems: 10th International Conference, TACAS 2004, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2004, Barcelona, Spain, March 29 - April 2, 2004. Proceedings 8, 3 (2006), 229–247.
  2. Ulrich Junker . 2004 . QUICKXPLAIN: Preferred Explanations and Relaxations for Over-constrained Problems . In Proceedings of the 19th National Conference on Artifical Intelligence. AAAI Press, 167–172 . Ulrich Junker. 2004. QUICKXPLAIN: Preferred Explanations and Relaxations for Over-constrained Problems. In Proceedings of the 19th National Conference on Artifical Intelligence. AAAI Press, 167–172.
  3. Tomas Mikolov Ilya Sutskever Kai Chen Greg S Corrado and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems. 3111–3119. Tomas Mikolov Ilya Sutskever Kai Chen Greg S Corrado and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems. 3111–3119.
  4. 10.1109/ICSE.2017.44 · DOI

Cited by

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Metadata

Authors
Wang, K., Singh, R., & Su, Z.
Affiliations
  • University of California at Davis, USA
  • Microsoft Research, USA
Venue
ACM SIGPLAN Notices
Publisher
Association for Computing Machinery (ACM)
Published
2018-06-11
Volume
53
Issue
4
Pages
481-495
ISSN
  • 0362-1340
  • 1558-1160
DOI
10.1145/3296979.3192384
Cited by
17
References
27
Language
en
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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CoChat. (2026). Citation check: Search, align, and repair: data-driven feedback generation for introductory programming exercises. https://app.cochat.ai/papers/10.1145/3296979.3192384
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Wang, K., Singh, R., & Su, Z. (2018). Search, align, and repair: data-driven feedback generation for introductory programming exercises. ACM SIGPLAN Notices. https://doi.org/10.1145/3296979.3192384

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.