A Lambda Model Characterizing Computational Behaviours of Terms

Σχετικά έγγραφα
About these lecture notes. Simply Typed λ-calculus. Types

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

C.S. 430 Assignment 6, Sample Solutions

Formal Semantics. 1 Type Logic

From the finite to the transfinite: Λµ-terms and streams

2 Composition. Invertible Mappings

The λ-calculus. Lecturer: John Wickerson. Phil Wadler

The Simply Typed Lambda Calculus

Sequent Calculi for the Modal µ-calculus over S5. Luca Alberucci, University of Berne. Logic Colloquium Berne, July 4th 2008

Example Sheet 3 Solutions

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

EE512: Error Control Coding

Reminders: linear functions

Finitary proof systems for Kozen s µ

Finite Field Problems: Solutions

New bounds for spherical two-distance sets and equiangular lines

Fractional Colorings and Zykov Products of graphs

ORDINAL ARITHMETIC JULIAN J. SCHLÖDER

Lecture 2. Soundness and completeness of propositional logic

Dynamic types, Lambda calculus machines Section and Practice Problems Apr 21 22, 2016

Every set of first-order formulas is equivalent to an independent set

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

Chap. 6 Pushdown Automata

Αλγόριθμοι και πολυπλοκότητα NP-Completeness (2)

On the Galois Group of Linear Difference-Differential Equations

Chapter 3: Ordinal Numbers

Congruence Classes of Invertible Matrices of Order 3 over F 2

Abstract Storage Devices

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in

Affine Weyl Groups. Gabriele Nebe. Summerschool GRK 1632, September Lehrstuhl D für Mathematik

Homomorphism in Intuitionistic Fuzzy Automata

5. Choice under Uncertainty

k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +

A Note on Intuitionistic Fuzzy. Equivalence Relation

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Cyclic or elementary abelian Covers of K 4

Generating Set of the Complete Semigroups of Binary Relations

Mean-Variance Analysis

Foundations of Computer Science ENGR 3520 Fall 2013 Thursday, Nov 21, 2013

Tridiagonal matrices. Gérard MEURANT. October, 2008

Homomorphism of Intuitionistic Fuzzy Groups

SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018

MINIMAL CLOSED SETS AND MAXIMAL CLOSED SETS

Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions

Divergence for log concave functions

Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1

Intuitionistic Fuzzy Ideals of Near Rings

Statistics 104: Quantitative Methods for Economics Formula and Theorem Review

Homework 8 Model Solution Section

Uniform Convergence of Fourier Series Michael Taylor

Matrices and Determinants

Overview. Transition Semantics. Configurations and the transition relation. Executions and computation

Lecture 21: Properties and robustness of LSE

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

Numerical Analysis FMN011

Other Test Constructions: Likelihood Ratio & Bayes Tests

Inverse trigonometric functions & General Solution of Trigonometric Equations

Second Order Partial Differential Equations

Commutative Monoids in Intuitionistic Fuzzy Sets

λρ-calculus 1. each λ-variable is a λρ-term, called an atom or atomic term; 2. if M and N are λρ-term then (MN) is a λρ-term called an application;

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β

Type Theory and Coq. Herman Geuvers. Principal Types and Type Checking

Quadratic Expressions

Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)

Main source: "Discrete-time systems and computer control" by Α. ΣΚΟΔΡΑΣ ΨΗΦΙΑΚΟΣ ΕΛΕΓΧΟΣ ΔΙΑΛΕΞΗ 4 ΔΙΑΦΑΝΕΙΑ 1

4.6 Autoregressive Moving Average Model ARMA(1,1)

Math221: HW# 1 solutions

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.

A Bonus-Malus System as a Markov Set-Chain. Małgorzata Niemiec Warsaw School of Economics Institute of Econometrics

The ε-pseudospectrum of a Matrix

Trace Semantics for Polymorphic References. GaLoP 16 April 3rd 2016

ST5224: Advanced Statistical Theory II

Bounding Nonsplitting Enumeration Degrees

Second Order RLC Filters

1. Introduction and Preliminaries.

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics

Dr. D. Dinev, Department of Structural Mechanics, UACEG

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013

Verification. Lecture 12. Martin Zimmermann

Introduction to Type Theory February 2008 Alpha Lernet Summer School Piriapolis, Uruguay. Herman Geuvers Nijmegen & Eindhoven, NL

THE SECOND ISOMORPHISM THEOREM ON ORDERED SET UNDER ANTIORDERS. Daniel A. Romano

ω ω ω ω ω ω+2 ω ω+2 + ω ω ω ω+2 + ω ω+1 ω ω+2 2 ω ω ω ω ω ω ω ω+1 ω ω2 ω ω2 + ω ω ω2 + ω ω ω ω2 + ω ω+1 ω ω2 + ω ω+1 + ω ω ω ω2 + ω

Ψηφιακή Επεξεργασία Φωνής

6.3 Forecasting ARMA processes

Test Data Management in Practice

The Probabilistic Method - Probabilistic Techniques. Lecture 7: The Janson Inequality

Durbin-Levinson recursive method

Derivation of Optical-Bloch Equations

derivation of the Laplacian from rectangular to spherical coordinates

The Properties of Fuzzy Relations

6.1. Dirac Equation. Hamiltonian. Dirac Eq.

b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!

Lecture 34 Bootstrap confidence intervals

w o = R 1 p. (1) R = p =. = 1

Srednicki Chapter 55

Trigonometric Formula Sheet

Approximation of distance between locations on earth given by latitude and longitude

MATHEMATICS. 1. If A and B are square matrices of order 3 such that A = -1, B =3, then 3AB = 1) -9 2) -27 3) -81 4) 81

Transcript:

A Lambda Model Characterizing Computational Behaviours of Terms joint paper with Silvia Ghilezan RPC 01, Sendai, October 26, 2001 1

Plan of the talk normalization properties inverse limit model Stone dualities type assignment system reducibility method replaceability 2

Normalization properties M N iff M β a normal form M HN iff M β λ x.yn M WN iff M β λx.n or M β xn Persistent normalization properties M PN iff MN N for all terms N in N M PHN iff MN HN for all terms N M PWN iff MN WN for all terms N 3

I λx.x, λx.xx, Y λf.(λx.f(xx))(λx.f(xx)), K λxy.x λx.x N, but / PWN, since (λx.x )I β / WN λx.y( ) PHN, but / N λx.x( ) HN, but / N and / PWN, since (λx.x( )) β ( ) / WN YK PWN, but / HN λx. WN, but / HN and / PWN, since (λx. )M β / WN 4

Λ WN PWN HN PHN N PN 5

Plan of the talk normalization properties inverse limit model Stone dualities type assignment system reducibility method replaceability 6

Functional Behaviours step function a b WN λd. if a d then b else PWN D = [D D] n IN ( }.{{.. } ) HN h ĥ h PHN ĥ ĥ N n (ĥ h) (ˆn n) PN ˆn ( ĥ) (n ˆn) n 7

ˆn ˆn ( ĥ) (n ˆn) ĥ n ĥ (ĥ h) (ˆn n) h ĥ h D 0 [D 0 D 0 ] i 0 (ˆn) = ( ĥ) (n ˆn) i 0 (n) = (ĥ h) (ˆn n) i 0 (ĥ) = ĥ i 0 (h) = ĥ h i 0 ( ) = 8

Main Theorem, Version I M PN iff [[M]] D ρˆn ˆn M N iff [[M]] D ρˆn n M PHN iff [[M]] D ρˆn ĥ M HN iff [[M]] D ρˆn h M PWN iff [[M]] D ρˆn n IN ( }.{{.. } ) n M WN iff [[M]] D ρˆn ρˆn (x) = ˆn 9

Plan of the talk normalization properties inverse limit model Stone dualities type assignment system reducibility method replaceability 10

Stone dualities topological spaces as partial orders Stone spaces as Boolean algebras (Stone, 36) Scott domains as information systems (Scott, 82) ω-algebraic complete lattices as intersection type theories (Coppo et al., 84) SFP domains as pre-locales (Abramsky, 91) 11

d M τ 12

semantics of terms d M τ 13

type assignment d M τ 14

semantics of types M d τ 15

Stone duality d = [[M]] d [[τ]] M M : τ d τ 16

We can describe an inverse limit model D by taking: the types freely generated by closing (a set of atomic types corresponding to) the elements of D 0 under the function type constructor and the intersection type constructor ; the preorder between types induced by reversing the order in D 0 and by encoding the initial projection, according to the correspondence: function type constructor step function intersection type constructor join 17

Plan of the talk normalization properties inverse limit model Stone dualities type assignment system reducibility method replaceability 18

The set T of types T = ν ˆν µ ˆµ Ω T T T T mapping m : T D m(ν) = n m(ˆν) = ˆn m(µ) = h m(ˆµ) = ĥ m(ω) = m(σ τ) = m(σ) m(τ) m(σ τ) = m(σ) m(τ). 19

Preorder on T ˆν ν ˆν ˆµ ν µ ˆµ µ σ Ω σ Ω Ω Ω ˆν (Ω ˆµ) (ν ˆν) ν (ˆµ µ) (ˆν ν) ˆµ Ω ˆµ µ ˆµ µ σ σ σ σ, τ τ σ σ τ τ σ σ σ σ τ, τ ζ σ ζ σ τ σ, σ τ τ σ σ, τ τ σ τ σ τ (σ τ) (σ ζ) σ τ ζ σ τ is short for σ τ and τ σ. 20

The set F of filters A filter is a set X T such that: Ω X if σ τ and σ X, then τ X if σ, τ X, then σ τ X F is the set of filters over T X is the filter generated by X σ is {σ} 21

F, is an ω-algebraic complete lattice X T (X Y ) X Y Ω Y 22

F and D are isomorphic as ω-algebraic complete lattices m : F D m (X) = σ X m(σ) m ( σ) = m(σ) 23

The type assignment system (ax) Γ, x : σ x : σ (Ω) Γ M : Ω ( E) ( I) Γ M : σ τ Γ N : σ Γ MN : τ Γ, x : σ M : τ Γ λx.m : σ τ ( I) Γ M : σ Γ M : τ Γ M : σ τ ( ) Γ M : σ, Γ M : τ σ τ 24

Finitary logical description For any lambda term M and environment ρ : var D [[M]] D ρ = m ({τ T Γ = ρ. Γ M : τ}) where Γ = ρ if and only if (x : σ) Γ implies m(σ) ρ(x). If Γ M : τ and M = β N, then Γ N : τ 25

Main Theorem, Version II M PN iff Γˆν M : ˆν M N iff Γˆν M : ν M PHN iff Γˆν M : ˆµ M HN iff Γˆν M : µ M PWN iff Γˆν M : Ω n Ω for all n IN M WN iff Γˆν M : Ω Ω Γˆν = {x : ˆν x var} 26

Plan of the talk normalization properties inverse limit model Stone dualities type assignment system reducibility method replaceability 27

Proof of Reducibility method interpret types by suitable sets show soundness of the type assignment we consider Λ as the applicative structure whose domain is the set of lambda terms and where the application is just the application of terms 28

valuation of types [[ ]] : T 2 Λ [[ν]] = N [[ˆν]] = PN [[µ]] = HN [[ˆµ]] = PHN [[Ω]] = Λ [[σ τ]] = [[σ]] [[τ]] [[σ τ]] = [[σ]] [[τ]] = {M WN N [[σ]] MN [[τ]]} [[Ω Ω]] = {M WN N [[Ω]] MN [[Ω]]} = {M WN N Λ MN Λ} = WN n IN [[Ωn Ω]] = n IN [[Ωn Ω Ω]] = {M WN N [[Ω]] M N [[Ω Ω]]} = {M WN N Λ M N WN } = PWN 29

valuation of terms [[ ]] ρ : Λ Λ [[M]] ρ = M[x 1 := ρ(x 1 ),..., x n := ρ(x n )] where ρ : var Λ is a valuation of term variables in Λ FV(M) = {x 1,..., x n } 30

semantic satisfiability relation = ρ = M : τ iff [[M]] ρ [[τ]] ρ = Γ iff ( (x : σ) Γ) ρ = x : σ Γ = M : τ iff ( ρ = Γ) ρ = M : τ soundness Γ M : τ Γ = M : τ 31

Plan of the talk normalization properties inverse limit model Stone dualities type assignment system reducibility method replaceability 32

Proof of WN - M = β λx.n Γˆν N : Ω (Ω) Γˆν λx.n : Ω Ω ( I) 33

- M = β x N (ax) Γˆν x : ˆν ( ) Γˆν x : Ω Ω Ω Γˆν N : Ω Γˆν xn : Ω Ω (Ω) ( E) 34

PWN - for all n, there is N such that M = β λx 1... x n.n Γˆν N : Ω (Ω) Γˆν λx 1... x n.n : Ω n Ω ( I) 35

- M = β λ x.y N (ax) Γˆν y : ˆν ( ) Γˆν y : Ω Ω Ω (Ω) Γˆν N : Ω ( E) Γˆν yn : Ω Ω ( I) Γˆν λ x.yn : Ω Ω 36

HN M = β λ x.y N Γ = {z : ˆµ z x } {z : ˆν z var x } (ax) Γ y : ˆµ ( ) Γ y : Ω µ (Ω) Γ N : Ω ( E) Γ yn : µ ( I) Γ λ x.yn : ˆµ µ ( ) Γˆν λ x.yn : µ 37

PHN M = β λ x.yn y is free Γ = {z : Ω z x } {z : ˆν z var x } (ax) Γ y : ˆν ( ) Γ y : Ω ˆµ (Ω) Γ N : Ω ( E) Γ yn : ˆµ ( I) Γ λ x.yn : Ω ˆµ ( ) Γˆν λ x.yn : ˆµ 38

N - M = β x N Γˆν x : ˆν (ax) Γˆν x : ν ν. ( ) Γˆν N : ν Γˆν xn : ν (HI) ( E) 39

- M = β λx.n. (HI) Γˆν N : ν. ( I) (case HN ) Γˆν λx.n : ˆν ν Γˆν λx.n : µ ( I) Γˆν λx.n : (ˆν ν) µ ( ) Γˆν λx.n : ν 40

PN replaceable and non-replaceable variables In a normal form M: all occurrences of variables bound in the initial abstractions are replaceable all occurrences of free variables are non-replaceable if x N(λ z y.p ) is a subterm of M and the showed occurrence of x is replaceable then the occurrences of y in P are replaceable if x N(λ z y.p ) is a subterm of M and the showed occurrence of x is non-replaceable then the occurrences of y in P are non-replaceable 41

λx.a λy.x b λz.y z λt.c t 42

λx.a λy.x b λz.y z λt.c t 43

λx.a λy.x b λz.y z λt.c t 44

a normal form M PN iff in M all fathers of replaceable variables are non-replaceable λx.a : ˆν λy.x : ν b : ˆν λz.y : ˆν λt.c : ˆν z : ν t : ˆν 45