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Type Inclusion Constraints and Type Inference
 In Proceedings of the 1993 Conference on Functional Programming Languages and Computer Architecture
, 1993
"... We present a general algorithm for solving systems of inclusion constraints over type expressions. The constraint language includes function types, constructor types, and liberal intersection and union types. We illustrate the application of our constraint solving algorithm with a type inference sys ..."
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Cited by 230 (21 self)
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We present a general algorithm for solving systems of inclusion constraints over type expressions. The constraint language includes function types, constructor types, and liberal intersection and union types. We illustrate the application of our constraint solving algorithm with a type inference system for the lambda calculus with constants. In this system, every pure lambda term has a (computable) type and every term typable in the Hindley/Milner system has all of its Hindley/Milner types. Thus, the inference system is an extension of the Hindley/Milner system that can type a very large set of lambda terms. 1 Introduction Type inference systems for functional languages are based on solving systems of type constraints. The best known and most widely used type inference algorithm was first discovered by Hindley and later independently by Milner [Hin69, Mil78]. In its simplest form, the algorithm generates type equations from the program text and then solves the equations. If the equati...
Ultrafast aliasing analysis using CLA: a million lines of C code in a second
, 2001
"... We describe the design and implementation of a system for very fast pointsto analysis. On code bases of about a million lines of unpreprocessed C code, our system performs eldbased Andersenstyle pointsto analysis in less than a second and uses less than 10MB of memory. Our tw o main contributions ..."
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Cited by 136 (0 self)
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We describe the design and implementation of a system for very fast pointsto analysis. On code bases of about a million lines of unpreprocessed C code, our system performs eldbased Andersenstyle pointsto analysis in less than a second and uses less than 10MB of memory. Our tw o main contributions are a databasecentric analysis architecture called compilelinkanalyze (CLA), and a new algorithm for implementing dynamic transitive closure. Our pointsto analysis system is built into a forward datadependence analysis tool that is deployed within Lucent to help with consistent type modi cations to large legacy C code bases. 1.
Partial Online Cycle Elimination in Inclusion Constraint Graphs
 IN PROCEEDINGS OF THE 1998 ACM SIGPLAN CONFERENCE ON PROGRAMMING LANGUAGE DESIGN AND IMPLEMENTATION
, 1998
"... Many program analyses are naturally formulated and implemented using inclusion constraints. We present new results on the scalable implementation of such analyses based on two insights: first, that online elimination of cyclic constraints yields ordersofmagnitude improvements in analysis time for ..."
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Cited by 127 (14 self)
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Many program analyses are naturally formulated and implemented using inclusion constraints. We present new results on the scalable implementation of such analyses based on two insights: first, that online elimination of cyclic constraints yields ordersofmagnitude improvements in analysis time for large problems; second, that the choice of constraint representation affects the quality and efficiency of online cycle elimination. We present an analytical model that explains our design choices and show that the model's predictions match well with results from a substantial experiment.
Introduction to set constraintbased program analysis
 Science of Computer Programming
, 1999
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Set Constraints: Results, Applications and Future Directions
 In Second Workshop on the Principles and Practice of Constraint Programming
"... . Set constraints are a natural formalism for many problems that arise in program analysis. This paper provides a brief introduction to set constraints: what set constraints are, why they are interesting, the current state of the art, open problems, applications and implementations. 1 Introduction ..."
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Cited by 74 (4 self)
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. Set constraints are a natural formalism for many problems that arise in program analysis. This paper provides a brief introduction to set constraints: what set constraints are, why they are interesting, the current state of the art, open problems, applications and implementations. 1 Introduction Set constraints are a natural formalism for describing relationships between sets of terms of a free algebra. A set constraint has the form X ` Y , where X and Y are set expressions. Examples of set expressions are 0 (the empty set), ff (a setvalued variable), c(X; Y ) (a constructor application), and the union, intersection, or complement of set expressions. Recently, there has been a great deal of interest in program analysis algorithms based on solving systems of set constraints, including analyses for functional languages [AWL94, Hei94, AW93, AM91, JM79, MR85, Rey69], logic programming languages [AL94, HJ92, HJ90b, Mis84], and imperative languages [HJ91]. In these algorithms, sets of...
The complexity of set constraints
, 1993
"... Set constraints are relations between sets of terms. They have been used extensively in various applications in program analysis and type inference. We present several results on the computational complexity of solving systems of set constraints. The systems we study form a natural complexity hierar ..."
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Cited by 74 (11 self)
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Set constraints are relations between sets of terms. They have been used extensively in various applications in program analysis and type inference. We present several results on the computational complexity of solving systems of set constraints. The systems we study form a natural complexity hierarchy depending on the form of the constraint language.
Aggregate Structure Identification and its Application to Program Analysis
 In Symposium on Principles of Programming Languages
, 1999
"... In this paper, we describe an efficient algorithm for lazily decomposing aggregates such as records and arrays into simpler components based on the access patterns specific to a given program. This process allows us both to identify implicit aggregate structure not evident from declarative informati ..."
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Cited by 68 (3 self)
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In this paper, we describe an efficient algorithm for lazily decomposing aggregates such as records and arrays into simpler components based on the access patterns specific to a given program. This process allows us both to identify implicit aggregate structure not evident from declarative information in the program, and to simplify the representation of declared aggregates when references are made only to a subset of their components. We show that the structure identification process can be exploited to yield the following principal results:  A fast type analysis algorithm applicable to program maintenance applications such as date usage inference for the "Year 2000" problem.  An efficient algorithm for atomization of aggregates. Given a program, an aggregate atomization decomposes all of the data that can be manipulated by the program into a set of disjoint atoms such that each data reference can be modeled as one or more references to atoms without loss of semantic information. A...
Polymorphic versus monomorphic flowinsensitive pointsto analysis for C
 IN STATIC ANALYSIS SYMPOSIUM
, 2000
"... We carry out an experimental analysis for two of the design dimensions of flowinsensitive pointsto analysis for C: polymorphic versus monomorphic and equalitybased versus inclusionbased. Holding other analysis parameters fixed, we measure the precision of the four design points on a suite of be ..."
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Cited by 67 (3 self)
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We carry out an experimental analysis for two of the design dimensions of flowinsensitive pointsto analysis for C: polymorphic versus monomorphic and equalitybased versus inclusionbased. Holding other analysis parameters fixed, we measure the precision of the four design points on a suite of benchmarks of up to 90,000 abstract syntax tree nodes. Our experiments show that the benefit of polymorphism varies significantly with the underlying monomorphic analysis. For our equalitybased analysis, adding polymorphism greatly increases precision, while for our inclusionbased analysis, adding polymorphism hardly makes any difference. We also gain some insight into the nature of polymorphism in pointsto analysis of C. In particular, we find considerable polymorphism available in function parameters, but little or no polymorphism in function results, and we show how this observation explains our results.
Decidability of Systems of Set Constraints with Negative Constraints
 INFORMATION AND COMPUTATION
, 1994
"... Set constraints are relations between sets of terms. They have been used extensively in various applications in program analysis and type inference. Recently, several algorithms for solving general systems of positive set constraints have appeared. In this paper we consider systems of mixed posi ..."
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Cited by 56 (10 self)
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Set constraints are relations between sets of terms. They have been used extensively in various applications in program analysis and type inference. Recently, several algorithms for solving general systems of positive set constraints have appeared. In this paper we consider systems of mixed positive and negative constraints, which are considerably more expressive than positive constraints alone. We show that it is decidable whether a given such system has a solution. The proof involves a reduction to a numbertheoretic decision problem that may be of independent interest.
Conjunto: Constraint Logic Programming with Finite Set Domains
 Logic Programming  Proceedings of the 1994 International Symposium, pages 339358, Massachusetts Institute of Technology
, 1994
"... Combinatorial problems involving sets and relations are currently tackled by integer programming and expressed with vectors or matrices of 01 variables. This is efficient but not flexible and unnatural in problem formulation. Toward a natural programming of combinatorial problems based on sets, gra ..."
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Cited by 53 (3 self)
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Combinatorial problems involving sets and relations are currently tackled by integer programming and expressed with vectors or matrices of 01 variables. This is efficient but not flexible and unnatural in problem formulation. Toward a natural programming of combinatorial problems based on sets, graphs or relations, we define a new CLP language with set constraints. This language Conjunto 1 aims at combining the declarative aspect of Prolog with the efficiency of constraint solving techniques. We propose to constrain a set variable to range over finite set domains specified by lower and upper bounds for set inclusion. Conjunto is based on the inclusion and disjointness constraints applied to set expressions which comprise the union, intersection and difference symbols. The main contribution herein is the constraint handler which performs constraint propagation by applying consistency techniques over set constraints. 1 Introduction Various systems of set constraints have been define...