PLDI 2022 Co-Located Events
43nd ACM SIGPLAN International Conference on Programming Language Design and Implementation (PLDI 2022)

Title Page

Welcome from the Chairs

A Systematic Evaluation of Large Language Models of Code
Frank F. Xu, Uri Alon, Graham Neubig, and Vincent Josua Hellendoorn
(Carnegie Mellon University, USA)

Publisher's Version

A Graph Neural Network-Based Performance Model for Deep Learning Applications
Shikhar Singh, James Hegarty, Hugh Leather, and Benoit Steiner
(Meta, USA)

Publisher's Version

Productivity Assessment of Neural Code Completion
Albert Ziegler, Eirini Kalliamvakou, X. Alice Li, Andrew Rice, Devon Rifkin, Shawn Simister, Ganesh Sittampalam, and Edward Aftandilian
(GitHub, USA)

Publisher's Version

From Perception to Programs: Regularize, Overparameterize, and Amortize
Hao Tang and Kevin Ellis
(Cornell University, USA)

Publisher's Version

Predictive Synthesis of API-Centric Code
Daye Nam, Baishakhi Ray, Seohyun Kim, Xianshan Qu, and Satish Chandra
(Carnegie Mellon University, USA; Columbia University, USA; Meta, USA)

Publisher's Version

ExeBench: An ML-Scale Dataset of Executable C Functions
Jordi Armengol-Estapé, Jackson Woodruff, Alexander Brauckmann, José Wesley de Souza Magalhães, and Michael F. P. O'Boyle
(University of Edinburgh, UK)

Publisher's Version Archive submitted (330 kB) Info

Automatically Debugging AutoML Pipelines using Maro: ML Automated Remediation Oracle
Julian Dolby, Jason Tsay, and Martin Hirzel
(IBM Research, USA)

Publisher's Version

Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
Md Rafiqul Islam Rabin, Aftab Hussain, and Mohammad Amin Alipour
(University of Houston, USA)

Publisher's Version