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75
A mechanical proof of the Turing completeness of pure LISP
 In Automated Theorem Proving: After 25 Years, W.W. Bledsoe and D.W. Loveland, Eds., American Mathematical Society
, 1984
"... We describe a proof by a computer program of the Turing completeness of a computational paradigm akin to Pure LISP. That is, we define formally the notions of a Turing machine and of a version of Pure LISP and prove that anything that can be computed by a Turing machine can be computed by LISP. Whil ..."
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Cited by 13 (8 self)
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We describe a proof by a computer program of the Turing completeness of a computational paradigm akin to Pure LISP. That is, we define formally the notions of a Turing machine and of a version of Pure LISP and prove that anything that can be computed by a Turing machine can be computed by LISP
2 • Logic: QuantifierFree First Order Logic with Induction (think of Pure Lisp
"... without apply) ..."
Pure versus Impure Lisp
, 1996
"... : The aspect of purity versus impurity that we address involves the absence versus presence of mutation: the use of primitives (RPLACA and RPLACD in Lisp, setcar! and setcdr! in Scheme) that change the state of pairs without creating new pairs. It is well known that cyclic list structures can be c ..."
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Cited by 17 (0 self)
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be created by impure programs, but not by pure ones. In this sense, impure Lisp is "more powerful" than pure Lisp. If the inputs and outputs of programs are restricted to be sequences of atomic symbols, however, this difference in computability disappears. We shall show that if the temporal
PURE VERSUS IMPURE LISP
"... Abstract: The aspect of purity versus impurity that we address involves the absence versus presence of mutation: the use of primitives (RPLfLCA and RPLACD in Lisp, setcsr! and setcclr! in Scheme) that change the state of pairs without creating new pairs. It is well known that cyclic list structur ..."
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structures can be created by impure programs, but not by pure ones. In this sense, impure Lisp is “more powerful ” than pure Lisp. If the inputs and outputs of programs are restricted to be sequences of at ornic symbols, however, this difference in computability disappears. We shall show
Definitional interpreters for higherorder programming languages
 Reprinted from the proceedings of the 25th ACM National Conference
, 1972
"... Abstract. Higherorder programming languages (i.e., languages in which procedures or labels can occur as values) are usually defined by interpreters that are themselves written in a programming language based on the lambda calculus (i.e., an applicative language such as pure LISP). Examples include ..."
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Cited by 338 (2 self)
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Abstract. Higherorder programming languages (i.e., languages in which procedures or labels can occur as values) are usually defined by interpreters that are themselves written in a programming language based on the lambda calculus (i.e., an applicative language such as pure LISP). Examples include
The Evolution of Lisp
 ACM SIGPLAN Notices
, 1993
"... Lisp is the world's greatest programming languageor so its proponents think. The structure of Lisp makes it easy to extend the language or even to implement entirely new dialects without starting from scratch. Overall, the evolution of Lisp has been guided more by institutional rivalry, one ..."
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Cited by 56 (1 self)
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Lisp is the world's greatest programming languageor so its proponents think. The structure of Lisp makes it easy to extend the language or even to implement entirely new dialects without starting from scratch. Overall, the evolution of Lisp has been guided more by institutional rivalry, one
Notes on Pippenger's Comparison of Pure and Impure LISP
, 1996
"... any impureLISP program running in time t can be compiled into a pureLISP program running in time O(t log t): first implement the impureLISP operations using an array of size at most t. Then represent the array as a balanced binary tree, which can be done in pure LISP. The main result of the paper ..."
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any impureLISP program running in time t can be compiled into a pureLISP program running in time O(t log t): first implement the impureLISP operations using an array of size at most t. Then represent the array as a balanced binary tree, which can be done in pure LISP. The main result
LISP ProgramSize Complexity
, 1992
"... A theory of programsize complexity for something close to real LISP is sketched. 1 This paper should be called "On the length of programs for computing finite binary sequences in LISP," since it closely follows references [3] to [6]. But that's too long! Copyright c fl 1992, Elsevie ..."
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Cited by 5 (3 self)
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machine as is done in [1], it would be nice to use instead the size in characters of programs in a real computer programming language. In my book Algorithmic Information Theory [1] I make considerable use of a toy version of pure LISP constructed expressly for theoretical purposes. And in Section 5.1 [1
Prolog: The language and its implementation compared with Lisp
 ACM SIGPLAN Notices
, 1977
"... Prolog is a Simple but powerful programming language founded on symbolic logic. The basic computational mechanism is a pattern matching process ("unification") operating on general record structures ("terms " of logic). We briefly review the language and compare i ..."
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Cited by 39 (3 self)
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it especially with pure Lisp. The remainder of the paper discusses techniques for implementing Prolog efficiently; in particular we describe how to compile the patterns involved in the matching process. These techniques are as incorporated in our DECsystemlO Prolog compiler (written in Prolog). The code
Church: A language for generative models
 In UAI
, 2008
"... Formal languages for probabilistic modeling enable reuse, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal language for describing stochastic generative processes. Church is based on the Lisp model of lambda calculus, containing a pu ..."
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Cited by 141 (27 self)
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pure Lisp as its deterministic subset. The semantics of Church is defined in terms of evaluation histories and conditional distributions on such histories. Church also includes a novel language construct, the stochastic memoizer, which enables simple description of many complex nonparametric models
Results 1  10
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