程序代写代做 interpreter Lambda Calculus C CSE 307 – Principles of Programming Languages Stony Brook University http://www.cs.stonybrook.edu/~cse307

CSE 307 – Principles of Programming Languages Stony Brook University http://www.cs.stonybrook.edu/~cse307
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Functional Programming
 Function evaluation is the basic concept for a programming paradigm that has been implemented in functional programming languages.
 The language ML (“Meta Language”) was originally introduced in the 1970’s as part of a theorem proving system, and was intended for describing and implementing proof strategies in the Logic for Computable Functions (LCF) theorem prover (whose language, pplambda, a combination of the first-order predicate calculus and the simply typed polymorphic lambda calculus, had ML as its metalanguage)
 Standard ML of New Jersey (SML) is an implementation of ML.
 The basic mode of computation in SML is the definition and
application of functions.
(c) Paul Fodor (CS Stony Brook)
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Install Standard ML
 Download from: http://www.smlnj.org
 Start Standard ML:
Type sml from the shell (run command line in
Windows)
 Exit Standard ML:
Ctrl-Z underWindows  Ctrl-D under Unix/Mac
(c) Paul Fodor (CS Stony Brook)

Standard ML
 The basic cycle of SML activity has three parts:
read input from the user,
evaluate it,
print the computed value (or an error message).
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(c) Paul Fodor (CS Stony Brook)

First SML example
 SML prompt:

 Simple example:
– 3;
val it = 3 : int
 The first line contains the SML prompt, followed by an expression typed in by the user and ended by a semicolon.
 The second line is SML’s response, indicating the value of the input expression and its type.
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(c) Paul Fodor (CS Stony Brook)

SML Scripts
 SML scripts (.sml files) can be run in the interpreter using the “use” command.
 The argument to “use” is the path and filename for the sml script.
-use “myscript.sml”;
 SML scripts can contain block comments.  Open comments with: (*
 Close comments with: *)
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(c) Paul Fodor (CS Stony Brook)

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Interacting with SML
 SML has a number of built-in operators and data types.  it provides the standard arithmetic operators
– 3+2;
val it = 5 : int
 The Boolean values true and false are available, as are logical operators such as not (negation), andalso (conjunction), and orelse (disjunction).
– not(true);
val it = false : bool
– true andalso false;
val it = false : bool
(c) Paul Fodor (CS Stony Brook)

Types in SML
 As part of the evaluation process, SML determines the type of the output value using methods of type inference.
 Simple types include int, real, bool, char, and string.
 One can also associate identifiers with values
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– val five = 3+2;
val five = 5 : int
and thereby establish a new value binding,
– five;
val it = 5 : int
(c) Paul Fodor (CS Stony Brook)

string and char
– “a”;
val it = “a” : string
– #”a”;
val it = #”a” : char
– explode(“ab”);
val it = [#”a”,#”b”] : char list
– implode([#”a”,#”b”]);
val it = “ab” : string
– “abc” ^ “def” = “abcdef”;
val it = true : bool
– size (“abcd”);
val it = 4 : int
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(c) Paul Fodor (CS Stony Brook)

string and char
– String.sub(“abcde”,2);
val it = #”c” : char
– substring(“abcdefghij”,3,4);
val it = “defg” : string
– concat [“AB”,” “,”CD”];
val it = “AB CD” : string
– str(#”x”);
val it = “x” : string
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(c) Paul Fodor (CS Stony Brook)

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Conditional Expression
 SML does not have typical branching flow control constructs as they exist in imperative languages
 But, it does have a single line conditional expression, similar to the ones in Python and C.
 Syntax: if then else exp2
 The expression following the keyword if must evaluate to a
Boolean value.
 The type of the result of expressions exp1 and exp2 are general, but they must be the same, so that they overall type of the conditional expression is fixed.
(c) Paul Fodor (CS Stony Brook)

Function Definitions in SML
 The general form of a function definition in SML is: fun () =
;
 For example,
– fun double(x) = 2*x;
val double = fn : int -> int
declares double as a function from integers to integers, i.e., of typeint  int
 Apply a function to an argument of the wrong type results in an error message:
– double(2.0);
Error: operator and operand don’t agree …
(c) Paul Fodor (CS Stony Brook)
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Function Definitions in SML
 The user may also explicitly indicate types:
– fun max(x:int,y:int,z:int) =
if ((x>y) andalso (x>z)) then x
else (if (y>z) then y else z);
val max = fn : int * int * int -> int
– max(3,2,2);
val it = 3 : int
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(c) Paul Fodor (CS Stony Brook)

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Recursive Definitions
 Theuseofrecursivedefinitionsisamaincharacteristicoffunctional programming languages, and these languages encourage the use of recursion over iterative constructs such as while loops:
– fun factorial(x) = if x=0 then 1
else x*factorial(x-1);
val factorial = fn : int -> int
 ThedefinitionisusedbySMLtoevaluateapplicationsofthefunctionto specific arguments.
– factorial(5);
val it = 120 : int
– factorial(10);
val it = 3628800 : int
(c) Paul Fodor (CS Stony Brook)

Example: Greatest Common Divisor
 The greatest common divisor (gcd) of two positive integers can defined recursively based on the following observations:
gcd(n, n) = n,
gcd(m, n) = gcd(n – m, m), if m < n, and gcd(m, n) = gcd(m − n, n), if m > n.
 These identities suggest the following recursive definition:
– fun gcd(m,n):int = if m=n then n
else if m>n then gcd(m-n,n)
else gcd(m,n-m);
val gcd = fn : int * int -> int
– gcd(12,30); – gcd(1,20); val it = 6 : int val it = 1 : int
(c) Paul Fodor (CS Stony Brook)
– gcd(125,56345); val it = 5 : int
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More recursive functions
– fun exp(b,n) = if n=0 then 1.0
else b * exp(b,n-1);
val exp = fn : real * int -> real
– exp(2.0,10);
val it = 1024.0 : real
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(c) Paul Fodor (CS Stony Brook)

Tuples in SML
 In SML tuples are finite sequences of arbitrary but fixed length, where different components need not be of the same type.
– (1, “two”);
val it = (1,”two”) : int * string
– val t1 = (1,2,3);
val t1 = (1,2,3) : int * int * int
– val t2 = (4,(5.0,6));
val t2 = (4,(5.0,6)) : int * (real * int)
 The components of a tuple can be accessed by applying the built-in functions #i, where i is a positive number.
If a function #i is applied to a tuple val it = 1 : int withfewerthanicomponents,an
– #2(t2); errorresults.
val it = (5.0,6) : real * int
(c) Paul Fodor (CS Stony Brook)
– #1(t1);
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Polymorphic functions
– fun id x = x;
val id = fn : ‘a -> ‘a
– (id 1, id “two”);
val it = (1,”two”) : int * string
– fun fst(x,y) = x;
val fst = fn : ‘a * ‘b -> ‘a
– fun snd(x,y) = y;
val snd = fn : ‘a * ‘b -> ‘b
– fun switch(x,y) = (y,x);
val switch = fn : ‘a * ‘b -> ‘b * ‘a
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(c) Paul Fodor (CS Stony Brook)

Polymorphic functions
 ‘a means “any type”, while ”a means “any type that can be compared for equality” (see the concat function later which compares a polymorphic variable list with []).
 There will be a “Warning: calling polyEqual” that means that you’re comparing two values with polymorphic type for equality.
 Why does this produce a warning? Because it’s less efficient than comparing two values of known types for equality.
 How do you get rid of the warning? By changing your function to
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only work with a specific type instead of any type.
 Should you do that or care about the warning? Probably not. In most cases
having a function that can work for any type is more important than having the most efficient code possible, so you should just ignore the warning.
(c) Paul Fodor (CS Stony Brook)

Lists in SML
 A list in SML is a finite sequence of objects, all of the same type:
– [1,2,3];
val it = [1,2,3] : int list
– [true,false,true];
val it = [true,false,true] : bool list
– [[1,2,3],[4,5],[6]];
val it = [[1,2,3],[4,5],[6]] :
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int list list
 The last example is a list of lists of integers. (c) Paul Fodor (CS Stony Brook)

Lists in SML
 All objects in a list must be of the same type:
– [1,[2]];
Error: operator and operand don’t agree
 An empty list is denoted by one of the following expressions: – [];
val it = [] : ’a list
– nil;
val it = [] : ’a list
 Note that the type is described in terms of a type variable ’a. Instantiating the type variable, by types such as int, results in (different) empty lists of corresponding types.
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(c) Paul Fodor (CS Stony Brook)

Operations on Lists
 SMLprovidesvariousfunctionsformanipulatinglists.
 The function hd returns the first element of its argument list. – hd[1,2,3];
val it = 1 : int
– hd[[1,2],[3]];
val it = [1,2] : int list
Applying this function to the empty list will result in an error.
 The function tl removes the first element of its argument list and returns the remaining list.
– tl[1,2,3];
val it = [2,3] : int list
– tl[[1,2],[3]];
val it = [[3]] : int list list
 The application of this function to the empty list will also result in an
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error.
(c) Paul Fodor (CS Stony Brook)

Operations on Lists
 Lists can be constructed by the (binary) function :: (read
cons) that adds its first argument to the front of the second
argument.
– 5::[];
val it = [5] : int list
– 1::[2,3];
val it = [1,2,3] : int list
– [1,2]::[[3],[4,5,6,7]];
val it = [[1,2],[3],[4,5,6,7]] : int list list
The arguments must be of the right type (such that the result is a list of elements of the same type):
– [1]::[2,3];
Error: operator and operand don’t agree
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(c) Paul Fodor (CS Stony Brook)

Operations on Lists
 Lists can also be compared for equality: – [1,2,3]=[1,2,3];
val it = true : bool
– [1,2]=[2,1];
val it = false : bool
– tl[1] = [];
val it = true : bool
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(c) Paul Fodor (CS Stony Brook)

Defining List Functions
 Recursion is particularly useful for defining functions that process lists.
 For example, consider the problem of defining an SML function that takes as arguments two lists of the same type and returns the concatenated list.
 In defining such list functions, it is helpful to keep in mind that a list is either
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–anemptylist[] or – of the form x::y
(c) Paul Fodor (CS Stony Brook)

Concatenation
 In designing a function for concatenating two lists x and y we thus distinguish two cases, depending on the form of x:
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If x is an empty list [], then concatenating x with y yields just y.
If x is of the form x1::x2, then concatenating x with y is a list of the form x1::z, where z is the result of concatenating x2 with y.
We can be more specific by observing that
x = hd(x)::tl(x)
(c) Paul Fodor (CS Stony Brook)

Concatenation
– fun concat(x,y) = if x=[] then y
else hd(x)::concat(tl(x),y);
val concat = fn : ’’a list * ’’a list -> ’’a list
 Applying the function yields the expected results:
– concat([1,2],[3,4,5]);
val it = [1,2,3,4,5] : int list
– concat([],[1,2]);
val it = [1,2] : int list
– concat([1,2],[]);
val it = [1,2] : int list
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(c) Paul Fodor (CS Stony Brook)

Length
 The following function computes the length of its argument list: – fun length(L) = if (L=nil) then 0
else 1+length(tl(L));
val length = fn : ’’a list -> int
– length[1,2,3];
val it = 3 : int
– length[[5],[4],[3],[2,1]];
val it = 4 : int
– length[];
val it = 0 : int
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(c) Paul Fodor (CS Stony Brook)

doubleall
 The following function doubles all the elements in its argument list (of integers):
– fun doubleall(L) =
if L=[] then []
else (2*hd(L))::doubleall(tl(L));
val doubleall = fn : int list -> int list
– doubleall[1,3,5,7];
val it = [2,6,10,14] : int list
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(c) Paul Fodor (CS Stony Brook)

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Reversing a List
 Concatenation of lists, for which we gave a recursive definition, is actually a built-in operator in SML, denoted by the symbol @.
 We use this operator in the following recursive definition of a function that reverses a list.
– fun reverse(L) =
if L = nil then nil
else reverse(tl(L)) @ [hd(L)];
val reverse = fn : ’’a list -> ’’a list
– reverse [1,2,3];
val it = [3,2,1] : int list
This method is not efficient: O(n2) (c) Paul Fodor (CS Stony Brook)

Reversing a List
 This way (using an accumulator) is better: O(n) – fun reverse_helper(L,L2) =
if L = nil then L2
else reverse_helper(tl(L),hd(L)::L2);
– fun reverse(L) = reverse_helper(L,[]);
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(c) Paul Fodor (CS Stony Brook)

Removing List Elements
 The following function removes all occurrences of its first argument from its second argument list.
– fun remove(x,L) = if (L=[]) then []
else if x=hd(L)then remove(x,tl(L))
else hd(L)::remove(x,tl(L));
val remove = fn : ’’a * ’’a list -> ’’a list
– remove(1,[5,3,1]);
val it = [5,3] : int list
– remove(2,[4,2,4,2,4,2,2]);
val it = [4,4,4] : int list
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(c) Paul Fodor (CS Stony Brook)

Removing Duplicates
 The remove function can be used in the definition of another function that removes all duplicate occurrences of elements from its argument list:
– fun removedupl(L) =
if (L=[]) then []
else hd(L)::removedupl(remove(hd(L),tl(L)));
val removedupl = fn : ’’a list -> ’’a list
– removedupl([3,2,4,6,4,3,2,3,4,3,2,1]);
val it = [3,2,4,6,1] : int list
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(c) Paul Fodor (CS Stony Brook)

Records
 Records are structured data types of heterogeneous elements that are labeled
– {x=2, y=3};
 The order does not matter:
– {make=”Toyota”, model=”Corolla”, year=2017,
color=”silver”}
= {model=”Corolla”, make=”Toyota”, color=”silver”,
year=2017};
val it = true : bool
– fun full_name{first:string,last:string,
age:int,balance:real}:string =
first ^ ” ” ^ last;
(* ^ is the string concatenation operator *)
val full_name=fn:{age:int, balance:real, first:string,
last:string} -> string
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(c) Paul Fodor (CS Stony Brook)

Records
 We access fields of records using the “#” and the name of the field.
 Syntax:#();
 #make({make=”Toyota”,model=”Corolla”,year=2017,color=”silver”});
val it = “Toyota” : string
 Records can use numbers as names for fields.
 In fact, SML tuples are really just records with some syntactic sugar.
 t1 = (1, “abc”, 5.0);
val t1 = (1,”abc”,5.0) : int * string * real
 t2={1=1,2=”abc”,3=5.0};
val t2 = (1,”abc”,5.0) : int * string * real
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(c) Paul Fodor (CS Stony Brook)

Definition by Patterns
 In SML functions can also be defined via patterns.  The general form of such definitions is:
fun () =
| () =
| …
| () = ;
where the identifiers, which name the function, are all the same, all patterns are of the same type, and all expressions are of the same type.
 Example:
– fun reverse(nil) = nil
| reverse(x::xs) = reverse(xs) @ [x];
val reverse = fn : ’a list -> ’a list
(c) Paul Fodor (CS Stony Brook)
The patterns are inspected in order and the first
match determines the value of the function.
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Patterns: Concatenate
fun concat([], L) = L
|concat(x::Xs, L) = x::concat(Xs, L);
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(c) Paul Fodor (CS Stony Brook)

Patterns: Length
fun length([]) = 0
|length(x::Xs) = 1 + length(Xs);
fun length'([], N) = N
|length'(x::Xs, N) = length'(Xs, N + 1);
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(c) Paul Fodor (CS Stony Brook)

Patterns: doubleall
fun doubleall([]) = []
|doubleall(x::Xs) = (x * 2)::doubleall(Xs);
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(c) Paul Fodor (CS Stony Brook)

Patterns: Reverse
fun reverse([]) = []
|reverse(x::Xs) = reverse(Xs) @ [x];
fun reverse'([], R) = R
|reverse'(x::Xs, R) = reverse'(Xs, x::R);
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(c) Paul Fodor (CS Stony Brook)

Higher-Order Functions
 In functional programming languages functions can be used in definitions of other, so-called higher-order, functions.
 The following function, map, applies its first argument (a function) to all elements in its second argument (a list of suitable type):
– fun map(f,L) = if (L=[]) then [] else f(hd(L))::(map(f,tl(L)));
val map = fn : (’’a -> ’b) * ’’a list -> ’b list
 We may apply map with any function with the correct type as argument:
– fun square(x) = (x:int)*x;
val square = fn : int -> int
– map(square,[2,3,4]);
val it = [4,9,16] : int list
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(c) Paul Fodor (CS Stony Brook)

Higher-Order Functions
 More map examples
 Anonymous functions:
– map(fn x=>x+1, [1,2,3,4,5]);
val it = [2,3,4,5,6] : int list
– fun incr(list) = map (fn x=>x+1, list);
val incr = fn : int list -> int list
– incr[1,2,3,4,5];
val it = [2,3,4,5,6] : int list
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(c) Paul Fodor (CS Stony Brook)

Filter
 Filter: keep in a list only the values that satisfy some logical condition/boolean function
– fun filter(f,l) =
if l=[] then []
else if f(hd l)
then (hd l)::(filter (f, tl l))
else filter(f, tl l);
val filter = fn : (‘a -> bool) * ‘a list -> ‘a list
– filter((fn x => x>0), [~1,0,1]);
val it = [1] : int list
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(c) Paul Fodor (CS Stony Brook)

Permutations
– fun myInterleave(x,[]) = [[x]]
| myInterleave(x,h::t) =
(x::h::t)::(
map((fn l => h::l), myInterleave(x,t)));
– myInterleave(1,[]);
val it = [[1]] : int list list
– myInterleave(1,[2]);
val it = [[1,2],[2,1]] : int list list
– myInterleave(1,[2,3]);
val it = [[1,2,3],[2,1,3],[2,3,1]] : int list list
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(c) Paul Fodor (CS Stony Brook)

Permutations
– fun appendAll(nil) = nil
| appendAll(z::zs) = z @ (appendAll(zs));
– appendAll([[[1,2]],[[2,1]]]);
val it = [[1,2],[2,1]] : int list list
– fun permute(nil) = [[]]
| permute(h::t) = appendAll(
map((fn l => myInterleave(h,l)), permute(t)));
– permute([1,2,3]);
val it = [[1,2,3],[2,1,3],[2,3,1],[1,3,2],[3,1,2],
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[3,2,1]] : int list list
(c) Paul Fodor (CS Stony Brook)

Composition
 Composition is another example of a higher-order function: – fun comp(f,g)(x) = f(g(x));
val comp = fn : (‘a -> ‘b) * (‘c -> ‘a) -> ‘c -> ‘b
– val f = comp(Math.sin, Math.cos);
val f = fn : real -> real
SAME WITH:
– val g = Math.sin o Math.cos;
(* Composition “o” is predefined *)
val g = fn : real -> real
– f(0.25);
val it = 0.824270418114 : real
– g(0.25);
val it = 0.824270418114 : real
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(c) Paul Fodor (CS Stony Brook)

Mutually recursive function
definitions
– fun odd(n) = if n=0 then false
else even(n-1)
and
val odd = fn : int -> bool
val even = fn : int -> bool
– even(1);
val it = false : bool
– odd(1);
val it = true : bool
even(n) = if n=0 then true
else odd(n-1);
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(c) Paul Fodor (CS Stony Brook)

Splitting
 Wesplitalistbyapplyingtwofunctions,takeandskip,whichextractalternateelements; respectively, the elements at odd-numbered positions and the elements at even-numbered positions (if any).
 Thedefinitionsofthetwofunctionsmutuallydependoneachother,andhenceprovidean example of mutual recursion, as indicated by the SML-keyword and:
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– fun take(L) =
if L = nil then nil
else hd(L)::skip(tl(L))
and
skip(L) =
if L=nil then nil
else take(tl(L));
val take = fn : ’’a list -> ’’a list val skip = fn : ’’a list -> ’’a list – take[1,2,3,4,5,6,7];
val it = [1,3,5,7] : int list
– skip[1,2,3,4,5,6,7];
val it = [2,4,6] : int list
(c) Paul Fodor (CS Stony Brook)

Merging
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 Merge pattern definition:
– fun merge([],M) = M
| merge(L,[]) = L
| merge(x::xl,y::yl) =
if (x:int) int list
– merge([1,5,7,9],[2,3,5,5,10]);
val it = [1,2,3,5,5,5,7,9,10] : int list
– merge([],[1,2]);
val it = [1,2] : int list
– merge([1,2],[]);
val it = [1,2] : int list
(c) Paul Fodor (CS Stony Brook)

Sorting
 We next design a function for sorting a list of integers:  The function is recursive and based on a method
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known as Merge-Sort.
 To s o r t a l i s t L :
 first split L into two disjoint sublists (of about equal size),  then (recursively) sort the sublists, and
 finally merge the (now sorted) sublists.
This recursive method is known as Merge-Sort
 It requires suitable functions for
 splitting a list into two sublists AND
 merging two sorted lists into one sorted list (c) Paul Fodor (CS Stony Brook)

Merge Sort
– fun sort(L) =
if L=[] then []
else if tl(L)=[] then L
else merge(sort(take(L)),sort(skip(L)));
val sort = fn : int list -> int list
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(c) Paul Fodor (CS Stony Brook)

Currying
– fun f(a)(b)(c) = a+b+c;
val f = fn : int -> int -> int -> int
val f = fn : int -> (int -> (int -> int))
OR
– fun f a b c = a+b+c;
– val inc1 = f(1);
val inc1 = fn : int -> int -> int
val inc1 = fn : int -> (int -> int)
– val inc12 = inc1(2);
val inc12 = fn : int -> int
– inc12(3);
val it = 6 : int
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(c) Paul Fodor (CS Stony Brook)

McCarthy’s 91 function
 McCarthy’s 91 function:
– fun mc91(n) = if n>100 then n-10
else mc91(mc91(n+11));
val mc91 = fn : int -> int
– map mc91 [101, 100, 99, 98, 97, 96];
val it = [91,91,91,91,91,91] : int list
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(c) Paul Fodor (CS Stony Brook)

User defined data types
– datatype shape = Rectangle of real*real
| Circle of real
| Line of (real*real)list;
datatype shape
= Circle of real
| Line of (real * real) list
| Rectangle of real * real
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(c) Paul Fodor (CS Stony Brook)

Sets with lists in SML
fun member(X,L) =
if L=[] then false
else if X=hd(L) then true
else member(X,tl(L));
OR with patterns:
fun member(X,[]) = false
| member(X,Y::Ys) =
if (X=Y) then true
else member(X,Ys);
member(1,[1,2]); (* true *)
member(1,[2,1]); (* true *)
member(1,[2,3]); (* false *)
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(c) Paul Fodor (CS Stony Brook)

Sets – UNION
fun union(L1,L2) =
if L1=[] then L2
else if member(hd(L1),L2)
then union(tl(L1),L2)
else hd(L1)::union(tl(L1),L2);
union([1,5,7,9],[2,3,5,10]);
(* [1,7,9,2,3,5,10] *)
union([],[1,2]);
(* [1,2] *)
union([1,2],[]);
56
(* [1,2] *)
(c) Paul Fodor (CS Stony Brook)

Sets – UNION patterns
fun union([],L2) = L2
| union(X::Xs,L2) =
if member(X,L2) then union(Xs,L2)
else X::union(Xs,L2);
union([1,5,7,9],[2,3,5,10]);
(* [1,7,9,2,3,5,10] *)
union([],[1,2]);
(* [1,2] *)
union([1,2],[]);
57
(* [1,2] *)
(c) Paul Fodor (CS Stony Brook)

Sets – Intersection ∩
fun intersection(L1,L2) =
if L1=[] then []
else if member(hd(L1),L2)
then hd(L1)::intersection(tl(L1),L2)
else intersection(tl(L1),L2);
intersection([1,5,7,9],[2,3,5,10]);
(* [5] *)
58
(c) Paul Fodor (CS Stony Brook)

Sets – ∩ patterns
fun intersection([],L2) = []
| intersection(L1,[]) = []
| intersection(X::Xs,L2) =
if member(X,L2)
then X::intersection(Xs,L2)
else intersection(Xs,L2);
intersection([1,5,7,9],[2,3,5,10]);
(* [5] *)
59
(c) Paul Fodor (CS Stony Brook)

Sets – subset
fun subset(L1,L2) = if L1=[] then true
else if L2=[] then false
else if member(hd(L1),L2)
then subset(tl(L1),L2)
else false;
subset([1,5,7,9],[2,3,5,10]);
(* false *)
subset([5],[2,3,5,10]);
(* true *)
60
(c) Paul Fodor (CS Stony Brook)

Sets – subset patterns
fun subset([],L2) = true
| subset(L1,[]) = if(L1=[])
then true
else false
| subset(X::Xs,L2) =
if member(X,L2)
then subset(Xs,L2)
else false;
subset([1,5,7,9],[2,3,5,10]);
(* false *)
subset([5],[2,3,5,10]);
61
(* true *)(c) Paul Fodor (CS Stony Brook)

Sets – equals
fun setEqual(L1,L2) =
subset(L1,L2) andalso subset(L2,L1);
setEqual([1,5,7],[7,5,1,2]);
(* false *)
setEqual([1,5,7],[7,5,1]);
(* true *)
62
(c) Paul Fodor (CS Stony Brook)

Sets – Difference pat
fun minus([],L2) = []
| minus(X::Xs,L2) =
if member(X,L2)
then minus(Xs,L2)
else X::minus(Xs,L2);
minus([1,5,7,9],[2,3,5,10]);
(* [1,7,9] *)
63
(c) Paul Fodor (CS Stony Brook)

Sets – Cartesian product
fun product_one(X,[]) = []
| product_one(X,Y::Ys) =
(X,Y)::product_one(X,Ys);
product_one(1,[2,3]);
(* [(1,2),(1,3)] *)
fun product([],L2) = []
| product(X::Xs,L2) =
union(product_one(X,L2),
product(Xs,L2));
product([1,5,7,9],[2,3,5,10]);
64
(* [(1,2),(1,3),(1,5),(1,10),(5,2),
(5,3),(5,5),(5,10),(7,2),(7,3),…] *)
(c) Paul Fodor (CS Stony Brook)

Sets – Powerset
fun insert_all(E,L) =
if L=[] then []
else (E::hd(L)) :: insert_all(E,tl(L));
insert_all(1,[[],[2],[3],[2,3]]);
(* [ [1], [1,2], [1,3], [1,2,3] ] *)
fun powerSet(L) =
if L=[] then [[]]
else powerSet(tl(L)) @
insert_all(hd(L),powerSet(tl(L)));
powerSet([]);
powerSet([1,2,3]);
65powerSet([2,3]);
(c) Paul Fodor (CS Stony Brook)