Mon 15 Jun 2015 09:40 - 10:05 at PLDI Main BLUE (Portland 254-255) - Distinguished Papers Chair(s): Steve Blackburn

Type inference engines often give terrible error messages, and the more sophisticated the type system the worse the problem. We show that even with highly expressive type system implemented by the Glasgow Haskell Compiler (GHC)—including type classes, GADTs, and type families— it is possible to identify the most likely source of the type error, rather than the first source that the inference engine trips over. To determine which are the likely error sources, we apply a simple Bayesian model to a graph representa- tion of the typing constraints; the satisfiability or unsatis- fiability of paths within the graph provides evidence for or against possible explanations. While we build on prior work on error diagnosis for simpler type systems, inference in the richer type system of Haskell requires extending the graph with new nodes. The augmentation of the graph cre- ates challenges both for Bayesian reasoning and for ensuring termination. Using a large corpus of Haskell programs, we show that this error localization technique is practical and significantly improves accuracy over the state of the art.

Mon 15 Jun

Displayed time zone: Tijuana, Baja California change

09:00 - 11:00
Distinguished PapersResearch Papers at PLDI Main BLUE (Portland 254-255)
Chair(s): Steve Blackburn Australian National University
09:00
15m
Day opening
Opening and Welcome
Research Papers
Steve Blackburn Australian National University , David Grove IBM Research
09:15
25m
Talk
Automatically Improving Accuracy for Floating Point Expressions
Research Papers
Pavel Panchekha University of Washington, Alex Sanchez-Stern University of Washington, James R. Wilcox University of Washington, Zachary Tatlock University of Washington, Seattle
Media Attached
09:40
25m
Talk
Diagnosing Type Errors with Class
Research Papers
Danfeng Zhang Cornell University, Andrew C. Myers , Dimitrios Vytiniotis Microsoft Research, Cambridge, Simon Peyton Jones Microsoft Research, Cambridge
Media Attached
10:05
25m
Talk
Provably Correct Peephole Optimizations with Alive
Research Papers
Nuno P. Lopes Microsoft Research, David Menendez Rutgers University, Santosh Nagarakatte Rutgers University, John Regehr University of Utah
Pre-print Media Attached
10:30
20m
Talk
One Minute Madness
Research Papers