CSE341 Assignment  2 solution

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Write  the  functions  in  problem  1  –  3  in  a  single  file,  named  “sol2.sml”.   Then  upload  the  file  to  the  uni06.unist.ac.kr  server  (under  your  account),  run  the   following  command  in  the  same  directory  where  you  have  sol2.sml  file.            plsubmit assign2 sol2.sml     You  can  submit  the  file  multiple  times,  and  the  last  one  before  the  deadline  will  be   used  for  grading.  Please  test  submitting  your  solution  a  couple  of  days  before  the   deadline  to  make  sure  the  submission  works  for  you.  If  it  does  not  work,  please   contact  the  TA.       Problems     1. Simple  Eval  (10  pts)          We  define  a  simple  Propositional  Logic  as  following:   datatype expr = NUM of int | PLUS of expr * expr | MINUS of expr * expr datatype formula = TRUE | FALSE | NOT of formula | ANDALSO of formula * formula | ORELSE of formula * formula | IMPLY of formula * formula | LESS of expr * expr Write  eval  function  that  takes  a  formula  value  and  returns  the  Boolean  value  of  the   formula;  i.e.  the  function  has  the  following  type:     eval: formula – bool IMPLY is  defined  as  in  this  link:  http://mathworld.wolfram.com/Implies.html     2. Check  MetroMap  (10  pts)   We  define  a  data  type  representing  metropolitan  area  as  following:   datatype name = string datatype metro = STATION of name | AREA of name * metro
| CONNECT of metro * metro   Write  checkMetro  function  of  the  following  type:   checkMetro: metro – bool The  function  computes  if  the  given  metro  is  correctly  defined.  A  metro  is  correctly   defined  if  and  only  if  metro  STATION  names  appear  only  in  the  AREA  of  the  same   name.   For  example,  the  following  metros  are  correctly  defined:     AREA(“a”, STATION “a”) AREA(“a”, AREA(“a”, STATION “a”)) AREA(“a”, AREA(“b”, CONNECT(STATION “a”, STATION “b”))) AREA(“a”, CONNECT(STATION “a”, AREA(“b”, STATION “a”)))   Whereas,  the  following  metros  are  incorrectly  defined:   AREA(“a”, STATION “b”) AREA(“a”, AREA(“a”, STATION “b”)) AREA(“a”, AREA(“b”, CONNECT(STATION “a”, STATION “c”))) AREA(“a”, CONNECT(STATION “a”, AREA(“b”, STATION “c”)))   3. Lazy  List  (40  pts  –  (i)  20  pts,  (ii)  20  pts)   (i)    A  lazy  list  is  a  data  structure  for  representing  a  long  or  even  infinite  list.  In  SML  a   lazy  list  can  be  defined  as     datatype ‘a lazyList = nullList | cons of ‘a * (unit – ‘a lazyList) This  definition  says  that  lazy  lists  are  polymorphic,  having  a  type  of  ‘a.  A  value  of  a   lazy  list  is  either  nullList  or  a  cons  value  consisting  of  the  head  of  the  list  and  a   function  of  zero  arguments  that,  when  called,  will  return  a  lazy  list  representing  the   rest  of  the  list.  Write  the  following  functions  that  create  and  manipulate  lazy  lists:   • seq(first,  last) (4 pts) This function takes two integers and returns an integer lazy list containing the sequence of values first, first+1, … , last  • infSeq(first) (4 pts) This function takes an integer and returns an integer lazy list containing the infinite sequence of values first,first+1, …. • firstN(lazyListVal,n) (4 pts) This function takes a lazyList and an integer and returns an ordinary SML list containing the first n values in the lazyList. If the lazyList contains fewer than n values, then all the values in the lazyList are returned.
• Nth(lazyListVal,n) (4 pts) This function takes a lazyList and an integer and returns an option representing the n-th value in the lazyList (counting from 1). If the lazyList contains fewer than n values, then none is returned. (Recall that we defined ‘a option = some of ‘a | none). • filterMultiples(lazyListVal,n) (4 pts) This function returns a new lazy list that has n and all integer multiples of n removed from a lazyList. For example, a non-lazy list version of filterMultiples would behave as follows: filterMultiples([2,3,4,5,6],2) = [3,5] filterMultiples([3,4,5,6,7,8],3) = [4,5,7,8] (ii)  One  of  the  algorithms  to  compute  prime  numbers  is  the  “Sieve  of  Eratosthenes.”   The  algorithm  is  simple  as  following.   You start with the infinite list L = 2, 3, 4, 5, …. The head of this list (2) is a prime. If you filter out all values that are a multiple of 2, you get the list 3, 5, 7, 9, …. The head of this list (3) is a prime. Now you filter out all values that are a multiple of 3, you get the list 5, 7, 11, 13, 17, …. You repeatedly take the head of the resulting list as the next prime, and then filter from this list all multiples of the head value. Write primes() function that computes a lazyList containing all prime numbers starting from 2, using the “Sieve of Eratosthenes” technique. To test your function, evaluate firstN(primes(),10); you should get [2, 3, 5, 7, 11, 13, 17, 19, 23, 29]. Try Nth(primes(),20); you should get some 71. (This may take a few seconds to compute.) Hint: Create a recursive function sieve(lazyListVal) that returns a new lazyList. The first element of the cons in this lazyList should indicate the current value, as usual. The second value should be a function that calls sieve again appropriately.