Polymorphism, Subtyping, Whole Program Analysis and Accurate Data Types in Usage Analysis

There are a number of choices to be made in the designof a type based usage analysis. Some of these are: Should the analysis be monomorphic or have some degree of polymorphism? What aboutsubtyping? How should the analysis deal with user defined algebraic data types? Should it be a whole program analysis?Several researchers have speculated that these features are important but there has been a lack of empirical evidence. In this paper we present a systematic evaluation of each of these features in the context of a full scale implementation of a usage analysis for Haskell.Our measurements show that all features increase the precision. It is,however, not necessary to have them all to obtain an acceptable precision

Polymorphism, Subtyping, Whole Program Analysis and Accurate Data Types in Usage Analysis

There are a number of choices to be made in the design of a type based usage analysis. Some of these are: Should the analysis be monomorphic or have some degree of polymorphism? What aboutsubtyping? How should the analysis deal with user defined algebraic data types? Should it be a whole program analysis? Several researchers have speculated that these features are important but there has been a lack of empirical evidence. In this paper we present a systematic evaluation of each of these features in the context of a full scale implementation of a usage analysis for Haskell. Our measurements show that all features increase the precision. It is, however, not necessary to have them all to obtain an acceptable precision

Polymorphism, Subtyping, Whole Program Analysis and Accurate Data Types in Usage Analysis

Abstract. There are a number of choices to be made in the design of a type based usage analysis. Some of these are: Should the analysis be monomorphic or have some degree of polymorphism? What about subtyping? How should the analysis deal with user defined algebraic data types? Should it be a whole program analysis? Several researchers have speculated that these features are important but there has been a lack of empirical evidence. In this paper we present a systematic evaluation of each of these features in the context of a full scale implementation of a usage analysis for Haskell. Our measurements show that all features increase the precision. It is, however, not necessary to have them all to obtain an acceptable precision.