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ASE 2021
Sun 14 - Sat 20 November 2021 Australia
Wed 17 Nov 2021 12:00 - 12:20 at Kangaroo - Learning II Chair(s): John Grundy

In recent years, Neural Machine Translator (NMT) has shown promises in automatically editing source code. Typical NMT based code editor only considers the code that needs to be changed as input and suggests developers with a ranked list of patched code to choose from - where the correct one may not be always at the top of the list. While NMT based code editing systems generate a broad spectrum of plausible patches, the correct one depends on the developers’ requirement and often on the context where the patch is applied. Thus, if developers provide some hints, using natural language or providing patch context, NMT models can benefit from them.

As a proof of concept, in this research, we leverage three modalities of information: edit location, edit code context, commit messages (as a proxy of developers’ hint in natural language) to automatically generate edits with NMT models. To that end, we build MODIT, a multi-modal NMT based code editing engine. With in-depth investigation and analysis, we show that developers’ hint as an input modality can narrow the search space for patches and outperform state-of-the-art models to generate correctly patched code in top-1 position.

Wed 17 Nov

Displayed time zone: Hobart change

12:00 - 13:00
Learning IIResearch Papers / Industry Showcase at Kangaroo
Chair(s): John Grundy Monash University
On Multi-Modal Learning of Editing Source Code
Research Papers
Saikat Chakraborty Columbia University, Baishakhi Ray Columbia University
Learning Highly Recursive Input Grammars
Research Papers
Neil Kulkarni University of California, Berkeley, Caroline Lemieux Microsoft Research, Koushik Sen University of California at Berkeley
Link to publication Pre-print
Learning GraphQL Query Cost
Industry Showcase
Georgios Mavroudeas Rensselaer Polytechnic Institute, Guillaume Baudart Inria; ENS; PSL University, Alan Cha IBM Research, USA, Martin Hirzel IBM Research, Jim A. Laredo IBM Research, Malik Magdon-Ismail Rensselaer Polytechnic Institute, Louis Mandel IBM Research, USA, Erik Wittern IBM Research