CSE341: Programming Languages Lecture 2 Functions, Pairs, Lists. Zach Tatlock Winter 2018

Similar documents
Function definitions. CSE341: Programming Languages Lecture 2 Functions, Pairs, Lists. Example, extended. Some gotchas. Zach Tatlock Winter 2018

CSE341: Programming Languages Lecture 2 Functions, Pairs, Lists. Dan Grossman Fall 2011

Programming Languages Dan Grossman Welcome to the Class!

CSE 341: Programming Languages

CMSC 330: Organization of Programming Languages. Functional Programming with Lists

CSE341: Programming Languages Lecture 6 Nested Patterns Exceptions Tail Recursion. Zach Tatlock Winter 2018

Begin at the beginning

Recap from last time. Programming Languages. CSE 130 : Fall Lecture 3: Data Types. Put it together: a filter function

CMSC 330: Organization of Programming Languages. Functional Programming with Lists

Preparing for Class: Watch le Videos! What is an ML program?

Programming Languages

Tail Recursion: Factorial. Begin at the beginning. How does it execute? Tail recursion. Tail recursive factorial. Tail recursive factorial

News. Programming Languages. Recap. Recap: Environments. Functions. of functions: Closures. CSE 130 : Fall Lecture 5: Functions and Datatypes

Introduction to OCaml

Programming Languages

Side note: Tail Recursion. Begin at the beginning. Side note: Tail Recursion. Base Types. Base Type: int. Base Type: int

Racket. CSE341: Programming Languages Lecture 14 Introduction to Racket. Getting started. Racket vs. Scheme. Example.

CSE341: Programming Languages Lecture 4 Records, Datatypes, Case Expressions. Dan Grossman Spring 2013

Programming Languages

CS Lecture 5: Pattern Matching. Prof. Clarkson Fall Today s music: Puff, the Magic Dragon by Peter, Paul & Mary

Programming Languages

News. Programming Languages. Complex types: Lists. Recap: ML s Holy Trinity. CSE 130: Spring 2012

OCaml. ML Flow. Complex types: Lists. Complex types: Lists. The PL for the discerning hacker. All elements must have same type.

Programming Languages

Programming Languages

Lists. Prof. Clarkson Fall Today s music: "Blank Space" by Taylor Swift

Programming Languages

Programming Languages

Programming Languages

CSE 341, Autumn 2005, Assignment 3 ML - MiniML Interpreter

SML A F unctional Functional Language Language Lecture 19

Programming Languages

CSE 341 Section 5. Winter 2018

Programming Languages. Next: Building datatypes. Suppose I wanted. Next: Building datatypes 10/4/2017. Review so far. Datatypes.

sum: tree -> int sum_leaf: tree -> int sum_leaf: tree -> int Representing Trees Next: Lets get cosy with Recursion Sum up the leaf values. E.g.

Programming Languages. Datatypes

CSE341: Programming Languages Lecture 11 Type Inference. Dan Grossman Spring 2016

Functions. Nate Foster Spring 2018

CSE 130 Programming Languages. Lecture 3: Datatypes. Ranjit Jhala UC San Diego

Recap. Recap. If-then-else expressions. If-then-else expressions. If-then-else expressions. If-then-else expressions

Recap: ML s Holy Trinity. Story So Far... CSE 130 Programming Languages. Datatypes. A function is a value! Next: functions, but remember.

Plan (next 4 weeks) 1. Fast forward. 2. Rewind. 3. Slow motion. Rapid introduction to what s in OCaml. Go over the pieces individually

CSE 130 Programming Languages. Datatypes. Ranjit Jhala UC San Diego

Recap: ML s Holy Trinity

CSE 130 [Winter 2014] Programming Languages

Note that pcall can be implemented using futures. That is, instead of. we can use

CSE341 Autumn 2017, Midterm Examination October 30, 2017

OCaml. History, Variants. ML s holy trinity. Interacting with ML. Base type: Integers. Base type: Strings. *Notes from Sorin Lerner at UCSD*

CSE341: Programming Languages Lecture 7 First-Class Functions. Dan Grossman Winter 2013

A First Look at ML. Chapter Five Modern Programming Languages, 2nd ed. 1

Lists. Michael P. Fourman. February 2, 2010

CS109A ML Notes for the Week of 1/16/96. Using ML. ML can be used as an interactive language. We. shall use a version running under UNIX, called

Homework 3 COSE212, Fall 2018

CVO103: Programming Languages. Lecture 5 Design and Implementation of PLs (1) Expressions

Defining Functions. CSc 372. Comparative Programming Languages. 5 : Haskell Function Definitions. Department of Computer Science University of Arizona

Product types add could take a single argument of the product type int * int fun add(,y):int = +y; > val add = fn : int * int -> int add(3,4); > val i

CSE341: Programming Languages Winter 2018 Unit 5 Summary Zach Tatlock, University of Washington

A Second Look At ML. Chapter Seven Modern Programming Languages, 2nd ed. 1

COSE212: Programming Languages. Lecture 4 Recursive and Higher-Order Programming

CMSC 330: Organization of Programming Languages. OCaml Expressions and Functions

Part I: Written Problems

Mini-ML. CS 502 Lecture 2 8/28/08

A Brief Introduction to Standard ML

Lists. Adrian Groza. Department of Computer Science Technical University of Cluj-Napoca

Fall 2018 Stephen Brookes. LECTURE 2 Thursday, August 30

Tuples. CMSC 330: Organization of Programming Languages. Examples With Tuples. Another Example

PROGRAMMING IN HASKELL. Chapter 5 - List Comprehensions

Which of the following expressions has the type int list?

A Third Look At ML. Chapter Nine Modern Programming Languages, 2nd ed. 1

Redefinition of an identifier is OK, but this is redefinition not assignment; Thus

Any questions. Say hello to OCaml. Say hello to OCaml. Why readability matters. History, Variants. Plan (next 4 weeks)

CSE 341 : Programming Languages

If we have a call. Now consider fastmap, a version of map that uses futures: Now look at the call. That is, instead of

Programming Languages. Tail Recursion. CSE 130: Winter Lecture 8: NOT TR. last thing function does is a recursive call

Part I: Written Problems

Data Types. Guest Lecture: Andrew Myers Spring 2018

CSE341: Programming Languages Lecture 17 Implementing Languages Including Closures. Dan Grossman Autumn 2018

Informatics 1 Functional Programming Lecture 4. Lists and Recursion. Don Sannella University of Edinburgh

A quick introduction to SML

Haskell Introduction Lists Other Structures Data Structures. Haskell Introduction. Mark Snyder

CSE 341: Programming Languages

Patterns The Essence of Functional Programming

Datatype declarations

Background. CMSC 330: Organization of Programming Languages. Useful Information on OCaml language. Dialects of ML. ML (Meta Language) Standard ML

CSE 341 Sample Midterm #2

CSci 4223 Principles of Programming Languages

The List Datatype. CSc 372. Comparative Programming Languages. 6 : Haskell Lists. Department of Computer Science University of Arizona

CSci 4223 Lecture 12 March 4, 2013 Topics: Lexical scope, dynamic scope, closures

Functional Programming. Pure Functional Programming

COSE212: Programming Languages. Lecture 3 Functional Programming in OCaml

CS 360: Programming Languages Lecture 10: Introduction to Haskell

Functional Programming. Pure Functional Programming

Fall Lecture 3 September 4. Stephen Brookes

Booleans (aka Truth Values) Programming Languages and Compilers (CS 421) Booleans and Short-Circuit Evaluation. Tuples as Values.

Sometimes it s good to be lazy

Programming Languages and Compilers (CS 421)

INF121: Functional Algorithmic and Programming

CMSC 330, Fall 2013, Practice Problem 3 Solutions

Scheme as implemented by Racket

CSCE 314 TAMU Fall CSCE 314: Programming Languages Dr. Flemming Andersen. Haskell Functions

Transcription:

CSE341: Programming Languages Lecture 2 Functions, Pairs, Lists Zach Tatlock Winter 2018

Function definitions Functions: the most important building block in the whole course Like Java methods, have arguments and result But no classes, this, return, etc. Example function binding: (* Note: correct only if y>=0 *) fun pow (x : int, y : int) = if y=0 then 1 else x * pow(x,y-1) Note: The body includes a (recursive) function call: pow(x,y-1) 2

Example, extended fun pow (x : int, y : int) = if y=0 then 1 else x * pow(x,y-1) fun cube (x : int) = pow (x,3) val sixtyfour = cube 4 val fortytwo = pow(2,2+2) + pow(4,2) + cube(2) + 2 3

Some gotchas Three common gotchas Bad error messages if you mess up function-argument syntax The use of * in type syntax is not multiplication Example: int * int -> int In expressions, * is multiplication: x * pow(x,y-1) Cannot refer to later function bindings That s simply ML s rule Helper functions must come before their uses Need special construct for mutual recursion (later) 4

Recursion If you re not yet comfortable with recursion, you will be soon J Will use for most functions taking or returning lists Makes sense because calls to same function solve simpler problems Recursion more powerful than loops We won t use a single loop in ML Loops often (not always) obscure simple, elegant solutions 5

Function bindings: 3 questions Syntax: fun x0 (x1 : t1,, xn : tn) = e (Will generalize in later lecture) Evaluation: A function is a value! (No evaluation yet) Adds x0 to environment so later expressions can call it (Function-call semantics will also allow recursion) Type-checking: Adds binding x0 : (t1 * * tn) -> t if: Can type-check body e to have type t in the static environment containing: Enclosing static environment x1 : t1,, xn : tn x0 : (t1 * * tn) -> t (for recursion) (earlier bindings) (arguments with their types) 6

More on type-checking fun x0 (x1 : t1,, xn : tn) = e New kind of type: (t1 * * tn) -> t Result type on right The overall type-checking result is to give x0 this type in rest of program (unlike Java, not for earlier bindings) Arguments can be used only in e (unsurprising) Because evaluation of a call to x0 will return result of evaluating e, the return type of x0 is the type of e The type-checker magically figures out t if such a t exists Later lecture: Requires some cleverness due to recursion More magic after hw1: Later can omit argument types too 7

Function Calls A new kind of expression: 3 questions Syntax: e0 (e1,,en) (Will generalize later) Parentheses optional if there is exactly one argument Type-checking: If: e0 has some type (t1 * * tn) -> t e1 has type t1,, en has type tn Then: e0(e1,,en) has type t Example: pow(x,y-1) in previous example has type int 8

Function-calls continued Evaluation: e0(e1,,en) 1. (Under current dynamic environment,) evaluate e0 to a function fun x0 (x1 : t1,, xn : tn) = e Since call type-checked, result will be a function 2. (Under current dynamic environment,) evaluate arguments to values v1,, vn 3. Result is evaluation of e in an environment extended to map x1 to v1,, xn to vn ( An environment is actually the environment where the function was defined, and includes x0 for recursion) 9

Tuples and lists So far: numbers, booleans, conditionals, variables, functions Now ways to build up data with multiple parts This is essential Java examples: classes with fields, arrays Now: Tuples: fixed number of pieces that may have different types Then: Lists: any number of pieces that all have the same type Later: Other more general ways to create compound data 10

Pairs (2-tuples) Need a way to build pairs and a way to access the pieces Build: Syntax: (e1,e2) Evaluation: Evaluate e1 to v1 and e2 to v2; result is (v1,v2) A pair of values is a value Type-checking: If e1 has type ta and e2 has type tb, then the pair expression has type ta * tb A new kind of type 11

Pairs (2-tuples) Need a way to build pairs and a way to access the pieces Access: Syntax: #1 e and #2 e Evaluation: Evaluate e to a pair of values and return first or second piece Example: If e is a variable x, then look up x in environment Type-checking: If e has type ta * tb, then #1 e has type ta and #2 e has type tb 12

Examples Functions can take and return pairs fun swap (pr : int*bool) = (#2 pr, #1 pr) fun sum_two_pairs (pr1 : int*int, pr2 : int*int) = (#1 pr1) + (#2 pr1) + (#1 pr2) + (#2 pr2) fun div_mod (x : int, y : int) = (x div y, x mod y) fun sort_pair (pr : int*int) = if (#1 pr) < (#2 pr) then pr else (#2 pr, #1 pr) 13

Tuples Actually, you can have tuples with more than two parts A new feature: a generalization of pairs (e1,e2,,en) ta * tb * * tn #1 e, #2 e, #3 e, Homework 1 uses triples of type int*int*int a lot 14

Nesting Pairs and tuples can be nested however you want Not a new feature: implied by the syntax and semantics val x1 = (7,(true,9)) (* int * (bool*int) *) val x2 = #1 (#2 x1) (* bool *) val x3 = (#2 x1) (* bool*int *) val x4 = ((3,5),((4,8),(0,0))) (* (int*int)*((int*int)*(int*int)) *) 15

Lists Despite nested tuples, the type of a variable still commits to a particular amount of data In contrast, a list: Can have any number of elements But all list elements have the same type Need ways to build lists and access the pieces 16

Building Lists The empty list is a value: [] In general, a list of values is a value; elements separated by commas: [v1,v2,,vn] If e1 evaluates to v and e2 evaluates to a list [v1,,vn], then e1::e2 evaluates to [v,v1,,vn] e1::e2 (* pronounced "cons" *) 17

Accessing Lists Until we learn pattern-matching, we will use three standard-library functions null e evaluates to true if and only if e evaluates to [] If e evaluates to [v1,v2,,vn] then hd e evaluates to v1 (raise exception if e evaluates to []) If e evaluates to [v1,v2,,vn] then tl e evaluates to [v2,,vn] (raise exception if e evaluates to []) Notice result is a list 18

Type-checking list operations Lots of new types: For any type t, the type t list describes lists where all elements have type t Examples: int list bool list int list list (int * int) list (int list * int) list So [] can have type t list for any type t SML uses type 'a list to indicate this ( tick a or alpha ) For e1::e2 to type-check, we need a t such that e1 has type t and e2 has type t list. Then the result type is t list null : 'a list -> bool hd : 'a list -> 'a tl : 'a list -> 'a list 19

Example list functions fun sum_list (xs : int list) = if null xs then 0 else hd(xs) + sum_list(tl(xs)) fun countdown (x : int) = if x=0 then [] else x :: countdown (x-1) fun append (xs : int list, ys : int list) = if null xs then ys else hd (xs) :: append (tl(xs), ys) 20

Recursion again Functions over lists are usually recursive Only way to get to all the elements What should the answer be for the empty list? What should the answer be for a non-empty list? Typically in terms of the answer for the tail of the list! Similarly, functions that produce lists of potentially any size will be recursive You create a list out of smaller lists 21

Lists of pairs Processing lists of pairs requires no new features. Examples: fun sum_pair_list (xs : (int*int) list) = if null xs then 0 else #1(hd xs) + #2(hd xs) + sum_pair_list(tl xs) fun firsts (xs : (int*int) list) = if null xs then [] else #1(hd xs) :: firsts(tl xs) fun seconds (xs : (int*int) list) = if null xs then [] else #2(hd xs) :: seconds(tl xs) fun sum_pair_list2 (xs : (int*int) list) = (sum_list (firsts xs)) + (sum_list (seconds xs)) 22