InferType: A Compiler Toolkit for Implementing Efficient Constraint-Based Type Inference
This program is tentative and subject to change.
Supporting automatic type inference is in demand in modern language development. It is a challenging task but without appropriate supporting toolkits. This paper presents InferType, a Java library that helps implement constraint-based type inference. A compiler writer uses InferType’s classes and methods to describe type constraints and typing rules for type inference. InferType then performs constraint solving by translation to the Z3 SMT solver. InferType is equipped with our developed optimization technique. It reduces the search space for type variables by pre-computing the structures of those type variables for mitigating the performance bottleneck of constraint solving with deeply nested types. We use InferType to implement type inference for a subset of Python, and conduct experiments to evaluate how the developed optimization technique can affect the performance of type inference. Our results show that InferType’s optimization can greatly mitigate the performance bottleneck for programs with deeply nested types, and can potentially improve the performance for large nested types.
This program is tentative and subject to change.
Tue 17 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
15:30 - 17:00 | |||
15:30 15mTalk | InferType: A Compiler Toolkit for Implementing Efficient Constraint-Based Type Inference Technical Papers Senxi Li The University of Tokyo, Tetsuro Yamazaki University of Tokyo, Shigeru Chiba University of Tokyo | ||
15:45 15mTalk | A Sound Type System for Secure Currency Flow Technical Papers Luca Aceto Reykjavik University, Daniele Gorla Department of Computer Science, Sapienza University of Rome, Stian Lybech Reykjavik University | ||
16:00 15mTalk | Type Tailoring Technical Papers Ashton Wiersdorf University of Utah, Stephen Chang University of Massachusetts Boston, Matthias Felleisen Northeastern University, Ben Greenman University of Utah | ||
16:15 15mTalk | Learning Gradual Typing Performance Technical Papers Mohammad Wahiduzzaman Khan UL Lafayette, Sheng Chen University of Louisiana at Lafayette, Yi He Old Dominion University | ||
16:30 15mTalk | Generalizing Shape Analysis with Gradual Types Technical Papers Zeina Migeed University of California, Los Angeles, James Reed Fireworks AI, Jason Ansel Meta, Jens Palsberg University of California, Los Angeles (UCLA) | ||
16:45 15mTalk | Refinements for Multiparty Message-Passing Protocols: Specification-agnostic theory and implementation Technical Papers |