Paper Info
Title
Precise Constraint-Based Type Inference for Java
Abstract
Precise type information is invaluable for analysis and optimization of object-oriented programs. Some forms of polymorphism found in object-oriented languages pose significant difficulty for type inference, in particular data polymorphism. Agesen's Cartesian Product Algorithm (CPA) can analyze programs with parametric polymorphism in a reasonably precise and efficient manner, but CPAl oses precision for programs with data polymorphism. This paper presents a precise constraintbased type inference system for Java. It uses Data-Polymorphic CPA (DCPA), a novel constraint-based type inference algorithm which extends CPAwit h the ability to accurately and efficiently analyze data polymorphic programs. The system is implemented for the full Java language, and is used to statically verify the correctness of Java downcasts. Benchmark results are given which show that DCPAi s significantly more accurate than CPAan d the efficiency of DCPAis close to CPA.
Year
DOI
Venue
2001
10.1007/3-540-45337-7_6
ECOOP
Keywords
Field
DocType
java downcast,particular data polymorphism,precise constraintbased type inference,novel constraint-based type inference,type inference,data polymorphism,parametric polymorphism,data-polymorphic cpa,precise constraint-based type inference,precise type information,data polymorphic program,cartesian product,object oriented programming,polymorphism,object oriented language
Program optimization,Programming language,Inference,Object type,Computer science,Correctness,Parametric polymorphism,Type inference,Theoretical computer science,Program analysis,Java
Conference
ISBN
Citations 
PageRank 
3-540-42206-4
30
2.14
References 
Authors
10
2
Name
Order
Citations
PageRank
Tiejun Wang1302.14
Scott F. Smith269673.02