Componential set-based analysis
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
A practical subtyping system for Erlang
ICFP '97 Proceedings of the second ACM SIGPLAN international conference on Functional programming
Partial online cycle elimination in inclusion constraint graphs
PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
A framework for type inference with subtyping
ICFP '98 Proceedings of the third ACM SIGPLAN international conference on Functional programming
Type-based analysis of uncaught exceptions
Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Componential set-based analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
Type-based analysis of uncaught exceptions
ACM Transactions on Programming Languages and Systems (TOPLAS)
Regular expression types for XML
ICFP '00 Proceedings of the fifth ACM SIGPLAN international conference on Functional programming
The first-order theory of subtyping constraints
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Simplifying subtyping constraints: a theory
Information and Computation
Optimal Representations of Polymorphic Types with Subtyping
Higher-Order and Symbolic Computation
Entailment with Conditional Equality Constraints
ESOP '01 Proceedings of the 10th European Symposium on Programming Languages and Systems
Design and Correctness of Program Transformations Based on Control-Flow Analysis
TACS '01 Proceedings of the 4th International Symposium on Theoretical Aspects of Computer Software
Modular set-based analysis from contracts
Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Type reconstruction for general refinement types
ESOP'07 Proceedings of the 16th European conference on Programming
Existential label flow inference via CFL reachability
SAS'06 Proceedings of the 13th international conference on Static Analysis
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Constraint-based program analyses are appealing because elaborate analyses can be described with a concise and simple set of constraint generation rules. Constraint resolution algorithms have been developed for many kinds of constraints, conceptually allowing an implementation of a constraint-based program analysis to reuse large pieces of existing code. In practice, however, new analyses often involve re-implementing new, complex constraint solving frameworks, tuned for the particular analysis in question. This approach wastes development time and interferes with the desire to experiment quickly with a number of different analyses. We believe that implementing an analysis should require writing only the code to generate the constraints, and that a well engineered-library can take care of constraint representation, resolution, and transformation. Writing such a library capable of handling small programs is not too difficult, but scaling to large programs is hard. Toward this goal, we are developing a scalable, expressive framework for solving a class of set constraints. Scalability is achieved through four techniques: polymorphism, simplification, separation, and sparse representation of constraints.