The Semantics of Predicate Logic as a Programming Language
Journal of the ACM (JACM)
The denotational semantics of programming languages
Communications of the ACM
Denotational Semantics: The Scott-Strachey Approach to Programming Language Theory
Denotational Semantics: The Scott-Strachey Approach to Programming Language Theory
Complementary Definitions of Programming Language Semantics
Complementary Definitions of Programming Language Semantics
Automata, Languages, and Machines
Automata, Languages, and Machines
Introduction to Mathematical Theory of Computation
Introduction to Mathematical Theory of Computation
A Theory of Programming Language Semantics
A Theory of Programming Language Semantics
ACM Transactions on Programming Languages and Systems (TOPLAS)
A methodology for synthesis of recursive functional programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
The complexity of type inference for higher-order lambda calculi
POPL '91 Proceedings of the 18th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Data types as values: polymorphism, type-checking, encapsulation
POPL '78 Proceedings of the 5th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Some Reflections on Strachey and His Work
Higher-Order and Symbolic Computation
A Denotational Semantics of Defeasible Logic
CL '00 Proceedings of the First International Conference on Computational Logic
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Logic has been long interested in whether answers to certain questions are computable in principle, since the outcome puts bounds on the possibilities of formalization. More recently, precise comparisons in the efficiency of decision methods have become available through the developments in complexity theory. These, however, are applications to logic, and a big question is whether methods of logic have significance in the other direction for the more applied parts of computability theory.Programming languages offer an obvious opportunity as their syntactic formalization is well advanced; however, the semantical theory can hardly be said to be complete. Though we have many examples, we have still to give wide-ranging mathematical answers to these queries: What is a machine? What is a computable process? How (or how well) does a machine simulate a process? Programs naturally enter in giving descriptions of processes. The definition of the precise meaning of a program then requires us to explain what are the objects of computation (in a way, the statics of the problem) and how they are to be transformed (the dynamics).So far the theories of automata and of nets, though most interesting for dynamics, have formalized only a portion of the field, and there has been perhaps too much concentration on the finite-state and algebraic aspects. It would seem that the understanding of higher-level program features involves us with infinite objects and forces us to pass through several levels of explanation to go from the conceptual ideas to the final simulation on a real machine. These levels can be made mathematically exact if we can find the right abstractions to represent the necessary structures. The experience of many independent workers with the method of data types as lattices (or partial orderings) under an information content ordering, and with their continuous mappings, has demonstrated the flexibility of this approach in providing definitions and proofs, which are clean and without undue dependence on implementations. Nevertheless much remains to be done in showing how abstract conceptualizations can (or cannot) be actualized before we can say we have a unified theory.