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From ReductionBased to ReductionFree Normalization
, 2004
"... We present a systematic construction of a reductionfree normalization function. Starting from ..."
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Cited by 21 (8 self)
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We present a systematic construction of a reductionfree normalization function. Starting from
An operational foundation for delimited continuations in the CPS hierarchy
 Logical Methods in Computer Science
, 2005
"... Vol. 1 (2:5) 2005, pp. 1–39 www.lmcsonline.org ..."
Memoization in typedirected partial evaluation
 PROCEEDINGS OF THE 2002 ACM SIGPLAN/SIGSOFT CONFERENCE ON GENERATIVE PROGRAMMING AND COMPONENT ENGINEERING, NUMBER 2487 IN LECTURE NOTES IN COMPUTER SCIENCE
, 2002
"... We use a code generator—typedirected partial evaluation— to verify conversions between isomorphic types, or more precisely to verify that a composite function is the identity function at some complicated type. A typed functional language such as ML provides a natural support to express the function ..."
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Cited by 14 (6 self)
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We use a code generator—typedirected partial evaluation— to verify conversions between isomorphic types, or more precisely to verify that a composite function is the identity function at some complicated type. A typed functional language such as ML provides a natural support to express the functions and typedirected partial evaluation provides a convenient setting to obtain the normal form of their composition. However, offtheshelf typedirected partial evaluation turns out to yield gigantic normal forms. We identify that this gigantism is due to redundancies, and that these redundancies originate in the handling of sums, which uses delimited continuations. We successfully eliminate these redundancies by extending typedirected partial evaluation with memoization capabilities. The result only works for pure functional programs, but it provides an unexpected use of code generation and it yields ordersofmagnitude improvements both in time and in space for type isomorphisms.
Term rewriting for normalization by evaluation
 19–42, International Workshop on Implicit Computational Complexity (ICC’99
"... We extend normalization by evaluation ( rst presented in [5]) from the pure typedcalculus to general higher type term rewriting systems. We distinguish between computational rules and proper rewrite rules, and de ne a domain theoretic model intended to explain why normalization by evaluation for th ..."
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Cited by 12 (3 self)
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We extend normalization by evaluation ( rst presented in [5]) from the pure typedcalculus to general higher type term rewriting systems. We distinguish between computational rules and proper rewrite rules, and de ne a domain theoretic model intended to explain why normalization by evaluation for the former is much more e cient. Normalization by evaluation is proved to be correct w.r.t. this model. 1
A New OnePass Transformation into Monadic Normal Form
 COMPILER CONSTRUCTION, 12TH INTERNATIONAL CONFERENCE, CC 2003, NUMBER 2622 IN LECTURE NOTES IN COMPUTER SCIENCE
, 2003
"... ..."
Operational Aspects of Normalization by Evaluation
, 2001
"... A purely syntactic and untyped variant of Normalization by Evaluation for the calculus is presented in the framework of a twolevel calculus with rewrite rules to model the inverse of the evaluation functional. Among its operational properties gures a standardization theorem that formally establi ..."
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Cited by 3 (2 self)
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A purely syntactic and untyped variant of Normalization by Evaluation for the calculus is presented in the framework of a twolevel calculus with rewrite rules to model the inverse of the evaluation functional. Among its operational properties gures a standardization theorem that formally establishes adequacy of implementation in functional programming languages. An example implementation in Haskell is provided. The relation to usual typedirected Normalization by Evaluation is highlighted, using a short analysis of expansion that leads to a perspicuous strong normalization and conuence proof for "reduction as a byproduct.
A programming tutor for Haskell
 In Proceedings of CEFP 2011: Lecture Notes of the Central European School on Functional Programming, LNCS
, 2011
"... Abstract. In these lectures we will introduce an interactive system that supports writing simple functional programs. Using this system, students learning functional programming: – develop their programs incrementally, – receive feedback about whether or not they are on the right track, – can ask fo ..."
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Cited by 3 (3 self)
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Abstract. In these lectures we will introduce an interactive system that supports writing simple functional programs. Using this system, students learning functional programming: – develop their programs incrementally, – receive feedback about whether or not they are on the right track, – can ask for a hint when they are stuck, – see how a complete program is stepwise constructed, – get suggestions about how to refactor their program. The system itself is implemented as a functional program, and uses fundamental concepts such as rewriting, parsing, strategies, program transformations and higherorder combinators such as the fold. We will introduce these concepts, and show how they are used in the implementation of the interactive functional programming tutor. 1
Deriving a Statically Typed TypeDirected Partial Evaluator
 In Danvy [12
, 1999
"... Typedirected partial evaluation was originally implemented in Scheme, a dynamically typed language. It has also been implemented in ML, a statically HindleyMilner typed language. This note shows how the latter implementation can be derived from the former through a functional representation of ind ..."
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Typedirected partial evaluation was originally implemented in Scheme, a dynamically typed language. It has also been implemented in ML, a statically HindleyMilner typed language. This note shows how the latter implementation can be derived from the former through a functional representation of inductively dened types. 1 Introduction Typedirected partial evaluation is an approach to specializing a term written in a higherorder language. Such a higherorder term is specialized by normalizing it with respect to its type. Normalization is done by etaexpanding the term in a twolevel lambdacalculus and statically betareducing the expanded term. The two stages  etaexpansion and betareduction  share an intermediate result: a twolevel term. We consider two versions of the typedirected partial evaluation algorithm: (i) If the twolevel term is represented as a value of an inductively dened data type then the algorithm can be implemented in any (Turing complete) language. In thi...
Types for Proofs and Programs
, 1999
"... pport. Contents 1 Introduction and Overview 1 2 Types for Proofs 2 2.1 Formal Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.1 What is a Formal System? . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.2 The Origins of Formal Systems . . . . . . ..."
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pport. Contents 1 Introduction and Overview 1 2 Types for Proofs 2 2.1 Formal Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.1 What is a Formal System? . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.2 The Origins of Formal Systems . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.3 Formal Systems in Computer Science . . . . . . . . . . . . . . . . . . . . . 3 2.2 Theorem Proving: Making Formal Systems Usable . . . . . . . . . . . . . . . . . . 4 2.2.1 Objectives of Interactive Theorem Proving . . . . . . . . . . . . . . . . . . 4 2.2.2 How to Ensure Correctness . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2.3 How to Facilitate Denitions . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.4 How to Facilitate Reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3 Reasoning in HigherOrder Logic (HOL) . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3.1 Church's Si