Casts and Costs: Harmonizing Safety and Performance in Gradual Typing
Gradual typing allows programmers to use both static and dynamic typing in a single program. However, a well-known problem with sound gradual typing is that the interactions between static and dynamic code can cause significant performance degradation. These performance pitfalls are hard to predict and resolve, and discourage users from using gradual typing features. For example, when migrating to a more statically typed program, often adding a type annotation will trigger a slowdown that can be resolved by adding more annotations elsewhere, but since it’s not clear where the additional annotations must be added, the easier solution is to simply remove the annotation.
To address these problems, we develop: (1) a static cost semantics that accurately predicts the overhead of static-dynamic interactions in a gradually typed program, (2) a technique for efficiently inferring such costs for all combinations of inferrable type assignments in a program, and (3) a method for translating the results of this analysis into specific recommendations and explanations that can help programmers understand, debug, and optimize the performance of gradually typed programs. We have implemented our approach in Herder, a tool for statically analyzing the performance of different typing configurations for Reticulated Python programs. An evaluation on 15 Python programs shows that Herder can use this analysis to accurately and efficiently recommend type assignments that optimize the performance of these programs without sacrificing type safety.
Wed 26 SepDisplayed time zone: Guadalajara, Mexico City, Monterrey change
13:00 - 14:30
|A Spectrum of Type Soundness and Performance
|Casts and Costs: Harmonizing Safety and Performance in Gradual Typing
John Peter Campora ULL Lafayette, Sheng Chen University of Louisiana at Lafayette, Eric Walkingshaw Oregon State UniversityDOI
|Graduality from Embedding-Projection Pairs
|Ready, Set, Verify! Applying hs-to-coq to Real-World Haskell Code (Experience Report)
Joachim Breitner DFINITY Foundation, Antal Spector-Zabusky , Yao Li University of Pennsylvania, Christine Rizkallah University of New South Wales, John Wiegley BAE Systems, Stephanie Weirich University of Pennsylvania, USADOI