activity
20192022
most citedUnderstanding Neural Code Intelligence Through Program Simplification

38 citations · 67 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20228 cited

DiffusER: Discrete Diffusion via Edit-based Reconstruction

Machel Reid, Vincent J. Hellendoorn, Graham Neubig

In text generation, models that generate text from scratch one token at a time are currently the dominant paradigm. Despite being performant, these models lack the ability to revis…

cs.SE20224 cited

Comments on Comments: Where Code Review and Documentation Meet

Nikitha Rao, Jason Tsay, Martin Hirzel +1

A central function of code review is to increase understanding; helping reviewers understand a code change aids in knowledge transfer and finding bugs. Comments in code largely ser…

cs.PL202217 cited

A Systematic Evaluation of Large Language Models of Code

Frank F. Xu, Uri Alon, Graham Neubig +1

Large language models (LMs) of code have recently shown tremendous promise in completing code and synthesizing code from natural language descriptions. However, the current state-o…

cs.SE202138 cited

Understanding Neural Code Intelligence Through Program Simplification

Md Rafiqul Islam Rabin, Vincent J. Hellendoorn, Mohammad Amin Alipour

A wide range of code intelligence (CI) tools, powered by deep neural networks, have been developed recently to improve programming productivity and perform program analysis. To rel…

cs.SE2019

Are My Invariants Valid? A Learning Approach

Vincent J. Hellendoorn, Premkumar T. Devanbu, Oleksandr Polozov +1

Ensuring that a program operates correctly is a difficult task in large, complex systems. Enshrining invariants -- desired properties of correct execution -- in code or comments ca…