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Theoretical Computer Science - International Joint Conference on Theory and Practice of Software Development, P
A unified treatment of flow analysis in higher-order languages
POPL '95 Proceedings of the 22nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Lightweight closure conversion
ACM Transactions on Programming Languages and Systems (TOPLAS)
Infinitary control flow analysis: a collecting semantics for closure analysis
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Single and loving it: must-alias analysis for higher-order languages
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ACM Transactions on Programming Languages and Systems (TOPLAS)
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Higher-Order and Symbolic Computation
Abstract Compilation: A New Implementation Paradigm for Static Analysis
CC '96 Proceedings of the 6th International Conference on Compiler Construction
Modular set-based analysis from contracts
Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Improving flow analyses via ΓCFA: abstract garbage collection and counting
Proceedings of the eleventh ACM SIGPLAN international conference on Functional programming
A Posteriori Soundness for Non-deterministic Abstract Interpretations
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Semantics Engineering with PLT Redex
Semantics Engineering with PLT Redex
Abstracting abstract machines: a systematic approach to higher-order program analysis
Communications of the ACM
Family of abstract interpretations for static analysis of concurrent higher-order programs
SAS'11 Proceedings of the 18th international conference on Static analysis
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ACM Computing Surveys (CSUR)
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The technique of abstracting abstract machines (AAM) provides a systematic approach for deriving computable approximations of evaluators that are easily proved sound. This article contributes a complementary step-by-step process for subsequently going from a naive analyzer derived under the AAM approach, to an efficient and correct implementation. The end result of the process is a two to three order-of-magnitude improvement over the systematically derived analyzer, making it competitive with hand-optimized implementations that compute fundamentally less precise results.