Types for References, Exceptions and Continuations. Review of Subtyping. Γ e:τ τ <:σ Γ e:σ. Annoucements. How s the midterm going?

Size: px
Start display at page:

Download "Types for References, Exceptions and Continuations. Review of Subtyping. Γ e:τ τ <:σ Γ e:σ. Annoucements. How s the midterm going?"

Transcription

1 Types for References, Exceptions and Continuations Annoucements How s the midterm going? Meeting 21, CSCI 5535, Spring One-Slide Summary Review of Subtyping If τ is a subtype of σ then any expression of type τ can be used in a context that expects a σ; this is called subsumption. 4 Subsumption Formalize the requirements on subtyping Rule of subsumption If τ <: σ then an expression of type τ has type σ Γ e:τ τ <:σ Γ e:σ But now type safety may be in danger: If we say that int <: (int int) Then we can prove that 11 8 is well typed! There is a way to construct the subtyping relation to preserve type safety 5 Defining Subtyping The formal definition of subtyping is by inference rules for the judgment τ <: σ We start with subtyping on the base types e.g. int <: real or nat <: int These rules are language dependent and are typically based directly on types-as-sets arguments We then make subtyping a preorder (reflexive and transitive) τ 1 <:τ 2 τ 2 <:τ 3 τ <:τ τ 1 <:τ 3 Then we build-up subtyping for larger types 6 1

2 Subtyping for Functions Try τ <:σ τ <:σ So what do τ τ <:σ σ you think of Example Use: this rule? rounded_sqrt : R Z actual_sqrt : R R Since Z <: R, rounded_sqrt <: actual_sqrt So if I have code like this: float result = rounded_sqrt(5); // 2 I can replace it like this: float result = actual_sqrt(5); // 2.23 and everything will be fine. 7 Subtyping for Functions This rule is unsound Let Γ = f : int bool (and assume int <: real) We show using the above rule that Γ f 5.0 : bool But this is wrong since 5.0 is not a valid argument of f Γ f :int bool τ <:σ τ <:σ τ τ <:σ σ int<:real bool<:bool int bool<:real bool Γ f :real bool Γ f 5.0:bool Γ 5.0:real 8 Correct Function Subtyping We say that is covariant in the result type and contravariant in the argument type Informal correctness argument: Pick f : τ τ σ<:τ τ <:σ τ τ <:σ σ f expects an argument of type τ It also accepts an argument of type σ <: τ f returns a value of type τ Which can also be viewed as a σ (since τ <: σ ) End of Review On to Midterm Hints: References Hence f can be used as σ σ 9 Types for Imperative Features So far: types for pure functional languages Now: types for imperative features Such types are used to characterize non-local effects assignments exceptions Contextual semantics is useful here Just when you thought it was safe to forget it 11 References Such types are used for mutable memory cells Syntax (as in ML) e ::=... ref e : τ e 1 := e 2! e τ ::=... τ ref ref e : τ - evaluates e, allocates a new memory cell, stores the value of e in it and returns the address of the memory cell like malloc + initialization in C, or new in C++ and Java e 1 := e 2, evaluates e 1 to a memory cell and updates its value with the value of e 2! e - evaluates e to a memory cell and returns its contents 12 2

3 Global Effects, Reference Cells A reference cell can escape the static scope where it was created (λf:int int ref.!(f 5)) (λx:int. ref x : int) The value stored in a reference cell must be visible from the entire program The result of an expression must now include the changes to the heap that it makes (cf. IMP s opsem) To model reference cells we must extend the evaluation model 13 Modeling References A heap is a mapping from addresses to values h ::= h, a v : τ a Addresses, tag the heap cells with their types Types are useful only for static semantics. They are not needed for the evaluation, that is, are not a part of the implementation We call a program an expression with a heap p ::= heap h in e The initial program is heap in e Heap addresses act as bound variables in the expression This is a trick that allows easy reuse of properties of local variables for heap addresses e.g., we can rename the address and its occurrences at will 14 Static Semantics of References Contextual Semantics for References Rules for expressions: Γ e:τ Γ (refe:τ):τ ref Γ e 1 :τ ref Γ e 2 :τ Γ e 1 :=e 2 :unit Γ e:τ ref Γ!e:τ Rules for programs (new judgment): Γ v i :τ i (i=1...n) Γ e:τ heaphine:τ whereγ=a 1 :τ 1 ref,...,a n :τ n ref andh=a 1 v 1 :τ 1,...,a n v n :τ n 15 Addresses are values: v ::=... a New contexts: H ::= ref H H 1 := e 2 a 1 := H 2! H No new local reduction rules But some new global reduction rules heap h in H[ref v : τ] heap h, a v : τ in H[a] where a is fresh (this models allocation the heap is extended) heap h in H[! a] heap h in H[v] where a v : τ h (heap lookup can we get stuck?) heap h in H[a := v] heap h[a v] in H[*] where h[a v] means a heap like h except that the part a v 1 : τ in h is replaced by a v : τ (memory update) Global rules are used to propagate the effects of a write to the entire program (eval order matters!) 16 Contextual Semantics for References Example with References Addresses are values: v ::=... a New contexts: H ::= ref H H 1 := e 2 a 1 := H 2! H No new local reduction rules But some new global reduction rules heap h in H[ref v : τ] heap h, a v : τ in H[a] where a is fresh (this models allocation the heap is extended) heap h in H[! a] heap h in H[v] where a v : τ h (heap lookup can we get stuck?) heap h in H[a := v] heap h[a v] in H[*] where h[a v] means a heap like h except that the part a v 1 : τ in h is replaced by a v : τ (memory update) Global rules are used to propagate the effects of a write to the entire program (eval order matters!) 17 Consider these (the redex is underlined) heap in (λf:int int ref.!(f 5)) (λx:int. ref x : int) heap in!((λx:int. ref x : int) 5) heap in!(ref 5 : int) heap a = 5 : int in!a heap a = 5 : int in 5 The resulting program has a useless memory cell An equivalent result would be heap in 5 This is a simple way to model garbage collection 18 3

4 Subtyping for References? τ ref<:τ ref Midterm Exercise 5 Give a sound subtyping rule or explain why OR Say there is no sound rule and show potential rules are unsound Exceptions and Continuations 19 One-Slide Summary Exceptions are like non-local gotos; they are used to propagate errors. We will use contextual semantics to model them. Continuations allow you to take a snapshot of the current execution and store it for later use. They are often used for threads or backtracking. We will use contextual semantics to model them. Exceptions A mechanism that allows non-local control flow Useful for implementing the propagation of errors to caller Exceptions ensure* that errors are not ignored Compare with the manual error handling in C Languages with exceptions: C++, ML, Modula-3, Java, C#, We assume that there is a special type exn of exceptions exn could be int to model error codes In Java or C++, exn are special object types 21 * Supposedly. 22 Modeling Exceptions Syntax e ::=... raise e try e 1 handle x e 2 τ ::=... exn We ignore how exception values are created In examples we will use integers as exception values The handler binds x in e 2 to the actual exception value The raise expression never returns to the immediately enclosing context 1 + raise 2 is well-typed if (raise 2) then 1 else 2 is also well-typed (raise 2) 5 is also well-typed What should be the type of raise? 23 Example with Exceptions A (strange) factorial function let f = λx:int.λres:int. if x = 0 then raise res else f (x - 1) (res * x) in try f 5 1 handle x x The function returns in one step from the recursion The top-level handler catches the exception and turns it into a regular result 24 4

5 Typing Exceptions New typing rules Γ raisee:τ Γ trye 1 handlex= e 2 :τ 25 Typing Exceptions New typing rules Γ e:exn Γ raisee:τ Γ e 1 :τ Γ,x:exn e 2 :τ Γ trye 1 handlex= e 2 :τ A raise expression has an arbitrary type This is a clear sign that the expression does not return to its evaluation context The type of the body of try and of the handler must match Just like for conditionals 26 Dynamics of Exceptions Contexts for Exceptions For big-step, the result of evaluation can be an uncaught exception Evaluation answers: a ::= v uncaught v uncaught v has an arbitrary type remember HW2 For small-step, it is convenient to use contextual semantics Exceptions propagate through some contexts but not through others We distinguish the handling contexts that intercept exceptions (this will be new) 27 Contexts H :: = H e v H raise H try H handle x e Propagating contexts Contexts that propagate exceptions to their own enclosing contexts P ::= P e v P raise P (New) Decomposition theorem If e is not a value and e is well-typed then it can be decomposed in exactly one of the following ways: H[(λx:τ. e) v] (normal lambda calculus) H[try v handle x e] (handle it or not) H[try P[raise v] handle x e] (propagate!) P[raise v] (uncaught exception) 28 Exceptional Commentary The addition of exceptions preserves type soundness Exceptions are like non-local goto However, they cannot be used to implement recursion Thus we still cannot write (well-typed) nonterminating programs There are a number of ways to implement exceptions (e.g., zero-cost exceptions) 29 Continuations Some languages have a mechanism for taking a snapshot of the execution and storing it for later use Later the execution can be reinstated from the snapshot Useful for implementing threads, for example Examples: Scheme, LISP, ML, C (yes, really!) 30 5

6 Continuations Consider the expression: e 1 + e 2 in a context C How to express a snapshot of the execution right after evaluating e 1 but before evaluating e 2 and the rest of C? Idea: as a context C 1 = C [ + e 2 ] Alternatively, as λx 1. C [ x 1 + e 2 ] When we finish evaluating e 1 to v 1, we fill the context and continue with C[v 1 + e 2 ] But the C 1 continuation is still available and we can continue several times, with different replacements for e 1 31 Continuation Uses in Real Life You re walking and come to a fork in the road You save a continuation right for going right But you go left (with the right continuation in hand) You encounter Bender. Bender coerces you into joining his computer dating service. You save a continuation bad-date for going on the date. You decide to invoke the right continuation So, you go right (no evil date obligation, but with the baddate continuation in hand) A train hits you! On your last breath, you invoke the bad-date continuation 32 For Next Time Optional reading: Goodenough s classic paper on exception handling 33 6

Programming Languages Lecture 15: Recursive Types & Subtyping

Programming Languages Lecture 15: Recursive Types & Subtyping CSE 230: Winter 2008 Principles of Programming Languages Lecture 15: Recursive Types & Subtyping Ranjit Jhala UC San Diego News? Formalize first-order type systems Simple types (integers and booleans)

More information

Recursive Types and Subtyping

Recursive Types and Subtyping Recursive Types and Subtyping #1 One-Slide Summary Recall: Recursive types (e.g., τ list) make the typed lambda calculus as powerful as the untyped lambda calculus. If τ is a subtype of σ then any expression

More information

We defined congruence rules that determine the order of evaluation, using the following evaluation

We defined congruence rules that determine the order of evaluation, using the following evaluation CS 4110 Programming Languages and Logics Lectures #21: Advanced Types 1 Overview In this lecture we will extend the simply-typed λ-calculus with several features we saw earlier in the course, including

More information

Programming Languages

Programming Languages CSE 230: Winter 2008 Principles of Programming Languages Ocaml/HW #3 Q-A Session Push deadline = Mar 10 Session Mon 3pm? Lecture 15: Type Systems Ranjit Jhala UC San Diego Why Typed Languages? Development

More information

Recursive Types and Subtyping

Recursive Types and Subtyping Recursive Types and Subtyping #1 One-Slide Summary Recursive types (e.g., list) make the typed lambda calculus as powerful as the untyped lambda calculus. If is a subtype of then any expression of type

More information

Harvard School of Engineering and Applied Sciences CS 152: Programming Languages

Harvard School of Engineering and Applied Sciences CS 152: Programming Languages Harvard School of Engineering and Applied Sciences CS 152: Programming Languages Lecture 14 Tuesday, March 24, 2015 1 Parametric polymorphism Polymorph means many forms. Polymorphism is the ability of

More information

Harvard School of Engineering and Applied Sciences Computer Science 152

Harvard School of Engineering and Applied Sciences Computer Science 152 Harvard School of Engineering and Applied Sciences Computer Science 152 Lecture 17 Tuesday, March 30, 2010 1 Polymorph means many forms. Polymorphism is the ability of code to be used on values of different

More information

Mutable References. Chapter 1

Mutable References. Chapter 1 Chapter 1 Mutable References In the (typed or untyped) λ-calculus, or in pure functional languages, a variable is immutable in that once bound to a value as the result of a substitution, its contents never

More information

Programming Languages Lecture 14: Sum, Product, Recursive Types

Programming Languages Lecture 14: Sum, Product, Recursive Types CSE 230: Winter 200 Principles of Programming Languages Lecture 4: Sum, Product, Recursive Types The end is nigh HW 3 No HW 4 (= Final) Project (Meeting + Talk) Ranjit Jhala UC San Diego Recap Goal: Relate

More information

Simply-Typed Lambda Calculus

Simply-Typed Lambda Calculus #1 Simply-Typed Lambda Calculus #2 Back to School What is operational semantics? When would you use contextual (small-step) semantics? What is denotational semantics? What is axiomatic semantics? What

More information

CS-XXX: Graduate Programming Languages. Lecture 9 Simply Typed Lambda Calculus. Dan Grossman 2012

CS-XXX: Graduate Programming Languages. Lecture 9 Simply Typed Lambda Calculus. Dan Grossman 2012 CS-XXX: Graduate Programming Languages Lecture 9 Simply Typed Lambda Calculus Dan Grossman 2012 Types Major new topic worthy of several lectures: Type systems Continue to use (CBV) Lambda Caluclus as our

More information

Chapter 13: Reference. Why reference Typing Evaluation Store Typings Safety Notes

Chapter 13: Reference. Why reference Typing Evaluation Store Typings Safety Notes Chapter 13: Reference Why reference Typing Evaluation Store Typings Safety Notes References Computational Effects Also known as side effects. A function or expression is said to have a side effect if,

More information

Lecture 13: Subtyping

Lecture 13: Subtyping Lecture 13: Subtyping Polyvios Pratikakis Computer Science Department, University of Crete Type Systems and Programming Languages Pratikakis (CSD) Subtyping CS546, 2018-2019 1 / 15 Subtyping Usually found

More information

Subtyping. Lecture 13 CS 565 3/27/06

Subtyping. Lecture 13 CS 565 3/27/06 Subtyping Lecture 13 CS 565 3/27/06 Polymorphism Different varieties of polymorphism: Parametric (ML) type variables are abstract, and used to encode the fact that the same term can be used in many different

More information

Part III. Chapter 15: Subtyping

Part III. Chapter 15: Subtyping Part III Chapter 15: Subtyping Subsumption Subtype relation Properties of subtyping and typing Subtyping and other features Intersection and union types Subtyping Motivation With the usual typing rule

More information

CSE 505, Fall 2008, Final Examination 11 December Please do not turn the page until everyone is ready.

CSE 505, Fall 2008, Final Examination 11 December Please do not turn the page until everyone is ready. CSE 505, Fall 2008, Final Examination 11 December 2008 Please do not turn the page until everyone is ready. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

CSE 505: Concepts of Programming Languages

CSE 505: Concepts of Programming Languages CSE 505: Concepts of Programming Languages Dan Grossman Fall 2003 Lecture 6 Lambda Calculus Dan Grossman CSE505 Fall 2003, Lecture 6 1 Where we are Done: Modeling mutation and local control-flow Proving

More information

Formal Systems and their Applications

Formal Systems and their Applications Formal Systems and their Applications Dave Clarke (Dave.Clarke@cs.kuleuven.be) Acknowledgment: these slides are based in part on slides from Benjamin Pierce and Frank Piessens 1 Course Overview Introduction

More information

Part VI. Imperative Functional Programming

Part VI. Imperative Functional Programming Part VI Imperative Functional Programming Chapter 14 Mutable Storage MinML is said to be a pure language because the execution model consists entirely of evaluating an expression for its value. ML is

More information

Goal. CS152: Programming Languages. Lecture 15 Parametric Polymorphism. What the Library Likes. What The Client Likes. Start simpler.

Goal. CS152: Programming Languages. Lecture 15 Parametric Polymorphism. What the Library Likes. What The Client Likes. Start simpler. Goal Understand what this interface means and why it matters: CS152: Programming Languages Lecture 15 Parametric Polymorphism Dan Grossman Spring 2011 type a mylist; val mt_list : a mylist val cons : a

More information

Subsumption. Principle of safe substitution

Subsumption. Principle of safe substitution Recap on Subtyping Subsumption Some types are better than others, in the sense that a value of one can always safely be used where a value of the other is expected. Which can be formalized as by introducing:

More information

Tradeoffs. CSE 505: Programming Languages. Lecture 15 Subtyping. Where shall we add useful completeness? Where shall we add completeness?

Tradeoffs. CSE 505: Programming Languages. Lecture 15 Subtyping. Where shall we add useful completeness? Where shall we add completeness? Tradeoffs CSE 505: Programming Languages Lecture 15 Subtyping Zach Tatlock Autumn 2017 Desirable type system properties (desiderata): soundness - exclude all programs that get stuck completeness - include

More information

Part III Chapter 15: Subtyping

Part III Chapter 15: Subtyping Part III Chapter 15: Subtyping Subsumption Subtype relation Properties of subtyping and typing Subtyping and other features Intersection and union types Subtyping Motivation With the usual typing rule

More information

CMSC 336: Type Systems for Programming Languages Lecture 5: Simply Typed Lambda Calculus Acar & Ahmed January 24, 2008

CMSC 336: Type Systems for Programming Languages Lecture 5: Simply Typed Lambda Calculus Acar & Ahmed January 24, 2008 CMSC 336: Type Systems for Programming Languages Lecture 5: Simply Typed Lambda Calculus Acar & Ahmed January 24, 2008 Contents 1 Solution to the Exercise 1 1.1 Semantics for lambda calculus.......................

More information

Chapter 13: Reference. Why reference Typing Evaluation Store Typings Safety Notes

Chapter 13: Reference. Why reference Typing Evaluation Store Typings Safety Notes Chapter 13: Reference Why reference Typing Evaluation Store Typings Safety Notes References Mutability So far, what we discussed does not include computational effects (also known as side effects). In

More information

References and Exceptions. CS 565 Lecture 14 4/1/08

References and Exceptions. CS 565 Lecture 14 4/1/08 References and Exceptions CS 565 Lecture 14 4/1/08 References In most languages, variables are mutable: it serves as a name for a location the contents of the location can be overwritten, and still be

More information

Note that in this definition, n + m denotes the syntactic expression with three symbols n, +, and m, not to the number that is the sum of n and m.

Note that in this definition, n + m denotes the syntactic expression with three symbols n, +, and m, not to the number that is the sum of n and m. CS 6110 S18 Lecture 8 Structural Operational Semantics and IMP Today we introduce a very simple imperative language, IMP, along with two systems of rules for evaluation called small-step and big-step semantics.

More information

From IMP to Java. Andreas Lochbihler. parts based on work by Gerwin Klein and Tobias Nipkow ETH Zurich

From IMP to Java. Andreas Lochbihler. parts based on work by Gerwin Klein and Tobias Nipkow ETH Zurich From IMP to Java Andreas Lochbihler ETH Zurich parts based on work by Gerwin Klein and Tobias Nipkow 2015-07-14 1 Subtyping 2 Objects and Inheritance 3 Multithreading 1 Subtyping 2 Objects and Inheritance

More information

Second-Order Type Systems

Second-Order Type Systems #1 Second-Order Type Systems Homework 5 Summary Student : 37.9704 Student : 44.4466 ORIGINAL : 50.2442 Student : 50.8275 Student : 50.8633 Student : 50.9181 Student : 52.1347 Student : 52.1633 Student

More information

Variables. Substitution

Variables. Substitution Variables Elements of Programming Languages Lecture 4: Variables, binding and substitution James Cheney University of Edinburgh October 6, 2015 A variable is a symbol that can stand for another expression.

More information

CSE-321 Programming Languages 2010 Final

CSE-321 Programming Languages 2010 Final Name: Hemos ID: CSE-321 Programming Languages 2010 Final Prob 1 Prob 2 Prob 3 Prob 4 Prob 5 Prob 6 Total Score Max 18 28 16 12 36 40 150 There are six problems on 16 pages, including two work sheets, in

More information

Category Item Abstract Concrete

Category Item Abstract Concrete Exceptions To make things simple we ll first consider a simple failure mechanism. CMPSCI 630: Programming Languages Exceptions and Continuations Spring 2009 (with thanks to Robert Harper) Like exceptions,

More information

CSE 505, Fall 2007, Final Examination 10 December Please do not turn the page until everyone is ready.

CSE 505, Fall 2007, Final Examination 10 December Please do not turn the page until everyone is ready. CSE 505, Fall 2007, Final Examination 10 December 2007 Please do not turn the page until everyone is ready. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

Typed Lambda Calculus and Exception Handling

Typed Lambda Calculus and Exception Handling Typed Lambda Calculus and Exception Handling Dan Zingaro zingard@mcmaster.ca McMaster University Typed Lambda Calculus and Exception Handling p. 1/2 Untyped Lambda Calculus Goal is to introduce typing

More information

Subtyping (cont) Lecture 15 CS 565 4/3/08

Subtyping (cont) Lecture 15 CS 565 4/3/08 Subtyping (cont) Lecture 15 CS 565 4/3/08 Formalization of Subtyping Inversion of the subtype relation: If σ

More information

Type Systems. Pierce Ch. 3, 8, 11, 15 CSE

Type Systems. Pierce Ch. 3, 8, 11, 15 CSE Type Systems Pierce Ch. 3, 8, 11, 15 CSE 6341 1 A Simple Language ::= true false if then else 0 succ pred iszero Simple untyped expressions Natural numbers encoded as succ succ

More information

Foundations. Yu Zhang. Acknowledgement: modified from Stanford CS242

Foundations. Yu Zhang. Acknowledgement: modified from Stanford CS242 Spring 2013 Foundations Yu Zhang Acknowledgement: modified from Stanford CS242 https://courseware.stanford.edu/pg/courses/317431/ Course web site: http://staff.ustc.edu.cn/~yuzhang/fpl Reading Concepts

More information

CS152: Programming Languages. Lecture 7 Lambda Calculus. Dan Grossman Spring 2011

CS152: Programming Languages. Lecture 7 Lambda Calculus. Dan Grossman Spring 2011 CS152: Programming Languages Lecture 7 Lambda Calculus Dan Grossman Spring 2011 Where we are Done: Syntax, semantics, and equivalence For a language with little more than loops and global variables Now:

More information

CSE 505, Fall 2008, Final Examination 11 December Please do not turn the page until everyone is ready.

CSE 505, Fall 2008, Final Examination 11 December Please do not turn the page until everyone is ready. CSE 505, Fall 2008, Final Examination 11 December 2008 Please do not turn the page until everyone is ready. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

CS152: Programming Languages. Lecture 11 STLC Extensions and Related Topics. Dan Grossman Spring 2011

CS152: Programming Languages. Lecture 11 STLC Extensions and Related Topics. Dan Grossman Spring 2011 CS152: Programming Languages Lecture 11 STLC Extensions and Related Topics Dan Grossman Spring 2011 Review e ::= λx. e x e e c v ::= λx. e c τ ::= int τ τ Γ ::= Γ, x : τ (λx. e) v e[v/x] e 1 e 1 e 1 e

More information

Introduction to System F. Lecture 18 CS 565 4/20/09

Introduction to System F. Lecture 18 CS 565 4/20/09 Introduction to System F Lecture 18 CS 565 4/20/09 The Limitations of F 1 (simply-typed λ- calculus) In F 1 each function works exactly for one type Example: the identity function id = λx:τ. x : τ τ We

More information

Subtyping and Objects

Subtyping and Objects Subtyping and Objects Massimo Merro 20 November 2017 Massimo Merro Data and Mutable Store 1 / 22 Polymorphism So far, our type systems are very rigid: there is little support to code reuse. Polymorphism

More information

CSE505, Fall 2012, Midterm Examination October 30, 2012

CSE505, Fall 2012, Midterm Examination October 30, 2012 CSE505, Fall 2012, Midterm Examination October 30, 2012 Rules: The exam is closed-book, closed-notes, except for one side of one 8.5x11in piece of paper. Please stop promptly at Noon. You can rip apart

More information

MPRI course 2-4 Functional programming languages Exercises

MPRI course 2-4 Functional programming languages Exercises MPRI course 2-4 Functional programming languages Exercises Xavier Leroy October 13, 2016 Part I: Interpreters and operational semantics Exercise I.1 (**) Prove theorem 2 (the unique decomposition theorem).

More information

CS 242. Fundamentals. Reading: See last slide

CS 242. Fundamentals. Reading: See last slide CS 242 Fundamentals Reading: See last slide Syntax and Semantics of Programs Syntax The symbols used to write a program Semantics The actions that occur when a program is executed Programming language

More information

Featherweight Java (FJ)

Featherweight Java (FJ) x = 1 let x = 1 in... x(1).!x(1) x.set(1) Programming Language Theory Featherweight Java (FJ) Ralf Lämmel This lecture is based on David Walker s lecture: Computer Science 441, Programming Languages, Princeton

More information

Pierce Ch. 3, 8, 11, 15. Type Systems

Pierce Ch. 3, 8, 11, 15. Type Systems Pierce Ch. 3, 8, 11, 15 Type Systems Goals Define the simple language of expressions A small subset of Lisp, with minor modifications Define the type system of this language Mathematical definition using

More information

CS152: Programming Languages. Lecture 23 Advanced Concepts in Object-Oriented Programming. Dan Grossman Spring 2011

CS152: Programming Languages. Lecture 23 Advanced Concepts in Object-Oriented Programming. Dan Grossman Spring 2011 CS152: Programming Languages Lecture 23 Advanced Concepts in Object-Oriented Programming Dan Grossman Spring 2011 So far... The difference between OOP and records of functions with shared private state

More information

Operational Semantics. One-Slide Summary. Lecture Outline

Operational Semantics. One-Slide Summary. Lecture Outline Operational Semantics #1 One-Slide Summary Operational semantics are a precise way of specifying how to evaluate a program. A formal semantics tells you what each expression means. Meaning depends on context:

More information

GADTs meet Subtyping

GADTs meet Subtyping GADTs meet Subtyping Gabriel Scherer, Didier Rémy Gallium INRIA 2014 Gabriel Scherer, Didier Rémy (Gallium INRIA) GADTs meet Subtyping 2014 1 / 21 A reminder on GADTs GADTs are algebraic data types that

More information

Supplementary Notes on Exceptions

Supplementary Notes on Exceptions Supplementary Notes on Exceptions 15-312: Foundations of Programming Languages Frank Pfenning Lecture 9 September 25, 2002 In this lecture we first give an implementation of the C-machine for the fragment

More information

Whereweare. CS-XXX: Graduate Programming Languages. Lecture 7 Lambda Calculus. Adding data structures. Data + Code. What about functions

Whereweare. CS-XXX: Graduate Programming Languages. Lecture 7 Lambda Calculus. Adding data structures. Data + Code. What about functions Whereweare CS-XXX: Graduate Programming Languages Lecture 7 Lambda Calculus Done: Syntax, semantics, and equivalence For a language with little more than loops and global variables Now: Didn t IMP leave

More information

Type Inference Systems. Type Judgments. Deriving a Type Judgment. Deriving a Judgment. Hypothetical Type Judgments CS412/CS413

Type Inference Systems. Type Judgments. Deriving a Type Judgment. Deriving a Judgment. Hypothetical Type Judgments CS412/CS413 Type Inference Systems CS412/CS413 Introduction to Compilers Tim Teitelbaum Type inference systems define types for all legal programs in a language Type inference systems are to type-checking: As regular

More information

Gradual Typing for Functional Languages. Jeremy Siek and Walid Taha (presented by Lindsey Kuper)

Gradual Typing for Functional Languages. Jeremy Siek and Walid Taha (presented by Lindsey Kuper) Gradual Typing for Functional Languages Jeremy Siek and Walid Taha (presented by Lindsey Kuper) 1 Introduction 2 What we want Static and dynamic typing: both are useful! (If you re here, I assume you agree.)

More information

1 Introduction. 3 Syntax

1 Introduction. 3 Syntax CS 6110 S18 Lecture 19 Typed λ-calculus 1 Introduction Type checking is a lightweight technique for proving simple properties of programs. Unlike theorem-proving techniques based on axiomatic semantics,

More information

Review. CS152: Programming Languages. Lecture 11 STLC Extensions and Related Topics. Let bindings (CBV) Adding Stuff. Booleans and Conditionals

Review. CS152: Programming Languages. Lecture 11 STLC Extensions and Related Topics. Let bindings (CBV) Adding Stuff. Booleans and Conditionals Review CS152: Programming Languages Lecture 11 STLC Extensions and Related Topics e ::= λx. e x ee c v ::= λx. e c (λx. e) v e[v/x] e 1 e 2 e 1 e 2 τ ::= int τ τ Γ ::= Γ,x : τ e 2 e 2 ve 2 ve 2 e[e /x]:

More information

Types and Type Inference

Types and Type Inference Types and Type Inference Mooly Sagiv Slides by Kathleen Fisher and John Mitchell Reading: Concepts in Programming Languages, Revised Chapter 6 - handout on the course homepage Outline General discussion

More information

Type Systems Winter Semester 2006

Type Systems Winter Semester 2006 Type Systems Winter Semester 2006 Week 4 November 8 November 15, 2006 - version 1.1 The Lambda Calculus The lambda-calculus If our previous language of arithmetic expressions was the simplest nontrivial

More information

Type Systems Winter Semester 2006

Type Systems Winter Semester 2006 Type Systems Winter Semester 2006 Week 9 December 13 December 13, 2006 - version 1.0 Plan PREVIOUSLY: unit, sequencing, let, pairs, sums TODAY: 1. recursion 2. state 3.??? NEXT: exceptions? NEXT: polymorphic

More information

CSc 520 final exam Wednesday 13 December 2000 TIME = 2 hours

CSc 520 final exam Wednesday 13 December 2000 TIME = 2 hours NAME s GRADE Prob 1 2 3 4 5 I II III Σ Max 12 12 12 12 12 26 26 26 100(+... ) Score CSc 520 exam Wednesday 13 December 2000 TIME = 2 hours Write all answers ON THIS EXAMINATION, and submit it IN THE ENVELOPE

More information

INF 212 ANALYSIS OF PROG. LANGS FUNCTION COMPOSITION. Instructors: Crista Lopes Copyright Instructors.

INF 212 ANALYSIS OF PROG. LANGS FUNCTION COMPOSITION. Instructors: Crista Lopes Copyright Instructors. INF 212 ANALYSIS OF PROG. LANGS FUNCTION COMPOSITION Instructors: Crista Lopes Copyright Instructors. Topics Recursion Higher-order functions Continuation-Passing Style Monads (take 1) Identity Monad Maybe

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Fall 2016 Lecture 7a Andrew Tolmach Portland State University 1994-2016 Values and Types We divide the universe of values according to types A type is a set of values and a

More information

(Refer Slide Time: 4:00)

(Refer Slide Time: 4:00) Principles of Programming Languages Dr. S. Arun Kumar Department of Computer Science & Engineering Indian Institute of Technology, Delhi Lecture - 38 Meanings Let us look at abstracts namely functional

More information

11/6/17. Outline. FP Foundations, Scheme. Imperative Languages. Functional Programming. Mathematical Foundations. Mathematical Foundations

11/6/17. Outline. FP Foundations, Scheme. Imperative Languages. Functional Programming. Mathematical Foundations. Mathematical Foundations Outline FP Foundations, Scheme In Text: Chapter 15 Mathematical foundations Functional programming λ-calculus LISP Scheme 2 Imperative Languages We have been discussing imperative languages C/C++, Java,

More information

Operational Semantics of Cool

Operational Semantics of Cool Operational Semantics of Cool Key Concepts semantics: the meaning of a program, what does program do? how the code is executed? operational semantics: high level code generation steps of calculating values

More information

Dependent Types. Announcements. Project Presentations. Recap. Dependent Types. Dependent Type Notation

Dependent Types. Announcements. Project Presentations. Recap. Dependent Types. Dependent Type Notation Dependant Type Systems (saying what you are) a (hiding what you are) Meeting 25, CSCI 5535, Spring 2009 Announcements Project Presentations Let me know if you prefer Apr 27 or Apr 29 Small amount of extra

More information

CSE 341, Spring 2011, Final Examination 9 June Please do not turn the page until everyone is ready.

CSE 341, Spring 2011, Final Examination 9 June Please do not turn the page until everyone is ready. CSE 341, Spring 2011, Final Examination 9 June 2011 Please do not turn the page until everyone is ready. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

CSE 341: Programming Languages

CSE 341: Programming Languages CSE 341: Programming Languages Autumn 2005 Lecture 10 Mutual Recursion, Equivalence, and Syntactic Sugar CSE 341 Autumn 2005, Lecture 10 1 Mutual Recursion You ve already seen how multiple functions can

More information

CS 6110 S11 Lecture 25 Typed λ-calculus 6 April 2011

CS 6110 S11 Lecture 25 Typed λ-calculus 6 April 2011 CS 6110 S11 Lecture 25 Typed λ-calculus 6 April 2011 1 Introduction Type checking is a lightweight technique for proving simple properties of programs. Unlike theorem-proving techniques based on axiomatic

More information

Lambda Calculus. Variables and Functions. cs3723 1

Lambda Calculus. Variables and Functions. cs3723 1 Lambda Calculus Variables and Functions cs3723 1 Lambda Calculus Mathematical system for functions Computation with functions Captures essence of variable binding Function parameters and substitution Can

More information

Concepts of programming languages

Concepts of programming languages Concepts of programming languages Lecture 5 Wouter Swierstra 1 Announcements Submit your project proposal to me by email on Friday; The presentation schedule in now online Exercise session after the lecture.

More information

CSCI-GA Scripting Languages

CSCI-GA Scripting Languages CSCI-GA.3033.003 Scripting Languages 12/02/2013 OCaml 1 Acknowledgement The material on these slides is based on notes provided by Dexter Kozen. 2 About OCaml A functional programming language All computation

More information

1. true / false By a compiler we mean a program that translates to code that will run natively on some machine.

1. true / false By a compiler we mean a program that translates to code that will run natively on some machine. 1. true / false By a compiler we mean a program that translates to code that will run natively on some machine. 2. true / false ML can be compiled. 3. true / false FORTRAN can reasonably be considered

More information

Official Survey. Cunning Plan: Focus On Objects. The Need for a Calculus. Object Calculi Summary. Why Not Use λ-calculus for OO?

Official Survey. Cunning Plan: Focus On Objects. The Need for a Calculus. Object Calculi Summary. Why Not Use λ-calculus for OO? Modeling and Understanding Object-Oriented Oriented Programming Official Survey Please fill out the Toolkit course survey 40142 CS 655-1 Apr-21-2006 Midnight May-04-2006 9am Why not do it this evening?

More information

Lectures 24 and 25: Scheduling; Introduction to Effects

Lectures 24 and 25: Scheduling; Introduction to Effects 15-150 Lectures 24 and 25: Scheduling; Introduction to Effects Lectures by Dan Licata April 12 and 17, 2011 1 Brent s Principle In lectures 17 and 18, we discussed cost graphs, which can be used to reason

More information

COS 320. Compiling Techniques

COS 320. Compiling Techniques Topic 5: Types COS 320 Compiling Techniques Princeton University Spring 2016 Lennart Beringer 1 Types: potential benefits (I) 2 For programmers: help to eliminate common programming mistakes, particularly

More information

Region Analysis for Imperative Languages

Region Analysis for Imperative Languages Region Analysis for Imperative Languages Radu Rugina and Sigmund Cherem Computer Science Department Cornell University Ithaca, NY 14853 {rugina,siggi}@cs.cornell.edu Abstract This paper presents a region

More information

Subtyping (cont) Formalization of Subtyping. Lecture 15 CS 565. Inversion of the subtype relation:

Subtyping (cont) Formalization of Subtyping. Lecture 15 CS 565. Inversion of the subtype relation: Subtyping (cont) Lecture 15 CS 565 Formalization of Subtyping Inversion of the subtype relation:! If "

More information

Type Inference; Parametric Polymorphism; Records and Subtyping Section and Practice Problems Mar 20-23, 2018

Type Inference; Parametric Polymorphism; Records and Subtyping Section and Practice Problems Mar 20-23, 2018 Harvard School of Engineering and Applied Sciences CS 152: Programming Languages Type Inference; Parametric Polymorphism; Records and Subtyping Mar 20-23, 2018 1 Type Inference (a) Recall the constraint-based

More information

Harvard School of Engineering and Applied Sciences CS 152: Programming Languages. Lambda calculus

Harvard School of Engineering and Applied Sciences CS 152: Programming Languages. Lambda calculus Harvard School of Engineering and Applied Sciences CS 152: Programming Languages Tuesday, February 19, 2013 The lambda calculus (or λ-calculus) was introduced by Alonzo Church and Stephen Cole Kleene in

More information

CS1622. Semantic Analysis. The Compiler So Far. Lecture 15 Semantic Analysis. How to build symbol tables How to use them to find

CS1622. Semantic Analysis. The Compiler So Far. Lecture 15 Semantic Analysis. How to build symbol tables How to use them to find CS1622 Lecture 15 Semantic Analysis CS 1622 Lecture 15 1 Semantic Analysis How to build symbol tables How to use them to find multiply-declared and undeclared variables. How to perform type checking CS

More information

CIS 500 Software Foundations Fall September 25

CIS 500 Software Foundations Fall September 25 CIS 500 Software Foundations Fall 2006 September 25 The Lambda Calculus The lambda-calculus If our previous language of arithmetic expressions was the simplest nontrivial programming language, then the

More information

Functional Languages and Higher-Order Functions

Functional Languages and Higher-Order Functions Functional Languages and Higher-Order Functions Leonidas Fegaras CSE 5317/4305 L12: Higher-Order Functions 1 First-Class Functions Values of some type are first-class if They can be assigned to local variables

More information

Types. Type checking. Why Do We Need Type Systems? Types and Operations. What is a type? Consensus

Types. Type checking. Why Do We Need Type Systems? Types and Operations. What is a type? Consensus Types Type checking What is a type? The notion varies from language to language Consensus A set of values A set of operations on those values Classes are one instantiation of the modern notion of type

More information

Polymorphic lambda calculus Princ. of Progr. Languages (and Extended ) The University of Birmingham. c Uday Reddy

Polymorphic lambda calculus Princ. of Progr. Languages (and Extended ) The University of Birmingham. c Uday Reddy 06-02552 Princ. of Progr. Languages (and Extended ) The University of Birmingham Spring Semester 2016-17 School of Computer Science c Uday Reddy2016-17 Handout 6: Polymorphic Type Systems 1. Polymorphic

More information

Once Upon a Polymorphic Type

Once Upon a Polymorphic Type Once Upon a Polymorphic Type Keith Wansbrough Computer Laboratory University of Cambridge kw217@cl.cam.ac.uk http://www.cl.cam.ac.uk/users/kw217/ Simon Peyton Jones Microsoft Research Cambridge 20 January,

More information

CSE-321 Programming Languages 2012 Midterm

CSE-321 Programming Languages 2012 Midterm Name: Hemos ID: CSE-321 Programming Languages 2012 Midterm Prob 1 Prob 2 Prob 3 Prob 4 Prob 5 Prob 6 Total Score Max 14 15 29 20 7 15 100 There are six problems on 24 pages in this exam. The maximum score

More information

Polymorphism. Lecture 19 CS 565 4/17/08

Polymorphism. Lecture 19 CS 565 4/17/08 Polymorphism Lecture 19 CS 565 4/17/08 The Limitations of F 1 (simply-typed λ- calculus) In F 1 each function works exactly for one type Example: the identity function id = λx:τ. x : τ τ We need to write

More information

Functional Programming. Pure Functional Programming

Functional Programming. Pure Functional Programming Functional Programming Pure Functional Programming Computation is largely performed by applying functions to values. The value of an expression depends only on the values of its sub-expressions (if any).

More information

Lambda Calculi With Polymorphism

Lambda Calculi With Polymorphism Resources: The slides of this lecture were derived from [Järvi], with permission of the original author, by copy & x = 1 let x = 1 in... paste or by selection, annotation, or rewording. [Järvi] is in turn

More information

Scope, Functions, and Storage Management

Scope, Functions, and Storage Management Scope, Functions, and Storage Management Implementing Functions and Blocks cs3723 1 Simplified Machine Model (Compare To List Abstract Machine) Registers Code Data Program Counter (current instruction)

More information

COMP 1130 Lambda Calculus. based on slides by Jeff Foster, U Maryland

COMP 1130 Lambda Calculus. based on slides by Jeff Foster, U Maryland COMP 1130 Lambda Calculus based on slides by Jeff Foster, U Maryland Motivation Commonly-used programming languages are large and complex ANSI C99 standard: 538 pages ANSI C++ standard: 714 pages Java

More information

CSE-321 Programming Languages 2011 Final

CSE-321 Programming Languages 2011 Final Name: Hemos ID: CSE-321 Programming Languages 2011 Final Prob 1 Prob 2 Prob 3 Prob 4 Prob 5 Prob 6 Total Score Max 15 15 10 17 18 25 100 There are six problems on 18 pages in this exam, including one extracredit

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Winter 2017 Lecture 7b Andrew Tolmach Portland State University 1994-2017 Values and Types We divide the universe of values according to types A type is a set of values and

More information

Dynamic Types, Concurrency, Type and effect system Section and Practice Problems Apr 24 27, 2018

Dynamic Types, Concurrency, Type and effect system Section and Practice Problems Apr 24 27, 2018 Harvard School of Engineering and Applied Sciences CS 152: Programming Languages Apr 24 27, 2018 1 Dynamic types and contracts (a) To make sure you understand the operational semantics of dynamic types

More information

CS4215 Programming Language Implementation. Martin Henz

CS4215 Programming Language Implementation. Martin Henz CS4215 Programming Language Implementation Martin Henz Thursday 15 March, 2012 2 Chapter 11 impl: A Simple Imperative Language 11.1 Introduction So far, we considered only languages, in which an identifier

More information

Lambda Calculus and Type Inference

Lambda Calculus and Type Inference Lambda Calculus and Type Inference Björn Lisper Dept. of Computer Science and Engineering Mälardalen University bjorn.lisper@mdh.se http://www.idt.mdh.se/ blr/ August 17, 2007 Lambda Calculus and Type

More information

CSE 505, Fall 2008, Midterm Examination 29 October Please do not turn the page until everyone is ready.

CSE 505, Fall 2008, Midterm Examination 29 October Please do not turn the page until everyone is ready. CSE 505, Fall 2008, Midterm Examination 29 October 2008 Please do not turn the page until everyone is ready. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

Lecture Note: Types. 1 Introduction 2. 2 Simple Types 3. 3 Type Soundness 6. 4 Recursive Types Subtyping 17

Lecture Note: Types. 1 Introduction 2. 2 Simple Types 3. 3 Type Soundness 6. 4 Recursive Types Subtyping 17 Jens Palsberg Sep 24, 1999 Contents Lecture Note: Types 1 Introduction 2 2 Simple Types 3 3 Type Soundness 6 4 Recursive Types 12 5 Subtyping 17 6 Decision Procedure for Subtyping 19 7 First-Order Unification

More information

Lambda Calculus: Implementation Techniques and a Proof. COS 441 Slides 15

Lambda Calculus: Implementation Techniques and a Proof. COS 441 Slides 15 Lambda Calculus: Implementation Techniques and a Proof COS 441 Slides 15 Last Time: The Lambda Calculus A language of pure functions: values e ::= x \x.e e e v ::= \x.e With a call-by-value operational

More information