Deep reinforcement learning for syntactic error repair in student programs

Gupta, R and Kanade, A and Shevade, S (2019) Deep reinforcement learning for syntactic error repair in student programs. In: 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, 27 January - 1 February 2019, Honolulu, pp. 930-937.

PDF EAAI_2019.pdf - Published Version Restricted to Registered users only Download (425kB) | Request a copy

Abstract

Novice programmers often struggle with the formal syntax of programming languages. In the traditional classroom setting, they can make progress with the help of real time feedback from their instructors which is often impossible to get in the massive open online course (MOOC) setting. Syntactic error repair techniques have huge potential to assist them at scale. Towards this, we design a novel programming language correction framework amenable to reinforcement learning. The framework allows an agent to mimic human actions for text navigation and editing. We demonstrate that the agent can be trained through self-exploration directly from the raw input, that is, program text itself, without either supervision or any prior knowledge of the formal syntax of the programming language. We evaluate our technique on a publicly available dataset containing 6975 erroneous C programs with typographic errors, written by students during an introductory programming course. Our technique fixes 1699 (24.4) programs completely and 1310 (18.8) program partially, outperforming DeepFix, a state-of-the-art syntactic error repair technique, which uses a fully supervised neural machine translation approach.

Item Type:	Conference Paper
Publication:	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Publisher:	AAAI Press
Additional Information:	The copyright for this article belongs to AAAI Press.
Keywords:	C (programming language); Computer aided language translation; Errors; Program translators; Reinforcement learning; Repair; Students; Syntactics, Classroom settings; Introductory programming course; Machine translations; Massive open online course; Novice programmer; Real-time feedback; State of the art; Typographic errors, Deep learning
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	02 Dec 2022 09:35
Last Modified:	02 Dec 2022 09:35
URI:	https://eprints.iisc.ac.in/id/eprint/78187

Actions (login required)

View Item