Generate an Object Constraint Language (OCL) specification for the following Java code, ensuring no repeated or redundant operations or classes:

Example 1: 

public class ANALYSIS_OF_ALGORITHMS_SET_2_ASYMPTOTIC_ANALYSIS{
static int M4( int arr[] , int n , int x ) {
  int i ;
  for ( i=0; i<n; i++) {
    if (arr[i]==x ) {
      return i ;
    }
  }
  return -1 ;
}
}

AgileUML: 

class ANALYSIS_OF_ALGORITHMS_SET_ASYMPTOTIC_ANALYSIS {
  static operation M4( arr : Sequence(int), n : int, x : int) : int
  pre: true
  post: true
  activity: (    
     var i : int ;
     i := 0 ; 
     while i < n do ( 
     (
       if (arr[i+1] = x) then 
       ( return i
 ) else skip ;
 )   ;     
         i := i + 1 ) ;
    return -1
 );

}

Classes 1/1
Operations 1/3
Statements 7/7
Variables 4/4
Total accuracy = 13/15

Consistency 13/13


Trained LLM: 

class ANALYSIS_OF_ALGORITHMS_SET_2_ASYMPTOTIC_ANALYSIS {
  static   operation M4( arr : Sequence(int), n : int, x : int) : int
  pre: true
  post: true
  activity: (     var i : int ;
         i := 0 ; while i < n do ( (     if (arr[i+1] = x) then (     return i ) else skip )  ;     i := i + 1 ) ;
     return -1 );
}
 <EOF>

Classes 1/1
Operations 3/3
Statements 6/7
Variables 3/4
Total accuracy = 13/15

Consistency 12/13


Untrained LLM: 

context ANALYSIS_OF_ALGORITHMS_SET_2_ASYMPTOTIC_ANALYSIS::M4(arr: Sequence(Integer), n: Integer, x: Integer) : Integer

-- Preconditions: 
-- 1. 'arr' must not be null and its length must be equal to 'n'.
-- 2. 'n' must be greater than or equal to zero, ensuring a valid input array length.

pre: arr->notEmpty() and n = arr->size() and n >= 0

-- Postconditions:
-- 1. If the element 'x' is present in 'arr', then the result must be the index of the first occurrence of 'x'.
-- 2. If 'x' is not found, the result must be -1.
-- 3. The result must be within the valid index range of 'arr' if 'x' is found.

post: if arr->includes(x) then
        result = arr->indexOf(x) - 1
      else
        result = -1
      endif

Classes 1/1
Operations 1/3
Variables 3/4
Statements 7/7
Accuracy = 12/15
(preconditions on n are wrong)

Consistency 9/11


Example 2: 

public class BINARY_SEARCH {
    static int M15(int arr[], int l, int r, int x) {
        if (r >= l) {
            int mid = l + (r - l) / 2;
            if (arr[mid] == x) 
               return mid;
            if (arr[mid] > x) 
               return M15(arr, l, mid-1, x);
            return M15(arr, mid + 1, r, x);
        }
        return -1;
    }
}


AgileUML: 

class BINARY_SEARCH {
  static operation M15( arr : Sequence(int), l : int, r : int, x : int) : int
  pre: true
  post: true
  activity: (     
    if (r >= l) then (
      var mid : int ; mid := l + (r - l) / 2 ;
      if (arr[mid+1] = x) then     
        return mid else skip ; 
      if (arr[mid+1] > x) then
        return M15(arr, l, mid - 1, x) else skip ; 
      return M15(arr, mid + 1, r, x) 
 ) else skip ; 
     return -1 
 );

}

Classes 1/1
Operations 1/3
Variables 5/5
Statements 8/8
Accuracy = 15/17

Consistency = 11/11


Trained LLM: 

class BINARY_SEARCH {
  static   operation M15( arr : Sequence(int), l : int, r : int, x : int) : int
  pre: true
  post: true
  activity: (     if (r >= l) then (     var mid : int ; mid := l + (r - l) / 2 ;
     if (arr[mid+1] = x) then 
     return mid else skip ;
     if (arr[mid+1] > x) then 
     return M15(arr, l, mid - 1, x) else skip ;
     return M15(arr, mid + 1, r, x) ) else skip ;
     return -1 );
}
 <EOF>

Classes 1/1
Operations 3/3
Variables 4/5
Statements 8/8
Accuracy = 16/17

Consistency = 15/16

Untrained LLM: 

context BINARY_SEARCH::M15(arr: Sequence(Integer), l: Integer, r: Integer, x: Integer) : Integer

-- Preconditions: 
-- 1. The array 'arr' must not be empty, and the left (`l`) and right (`r`) indices must be valid.
-- 2. The array 'arr' must be sorted in ascending order, as binary search only works on sorted arrays.
-- 3. 'l' must be less than or equal to 'r', ensuring a valid range for the search.
-- 4. The size of the array must match the constraints on 'r'.

pre: arr->notEmpty() and l >= 0 and r = arr->size() - 1 and
     arr->forAll(i,j | i < j implies arr->at(i) <= arr->at(j))

-- Postconditions:
-- 1. If the element 'x' is present in 'arr' within the range `l` to `r`, the result must be the index of 'x'.
-- 2. If the element 'x' is not found, the result must be -1.
-- 3. The result must be within the bounds of the array (i.e., between `l` and `r` inclusive) if `x` is found.

post: if arr->subSequence(l+1, r+1)->includes(x) then
        result = arr->indexOf(x) - 1
      else
        result = -1
      endif

Classes 1/1
Operations 1/3
Variables 4/5
Statements 8/8
Accuracy = 14/17
(precondition on r is wrong)

Consistency 7/8


Example 3: 


public class EQUILIBRIUM_INDEX_OF_AN_ARRAY_1 {
    static int M209(int arr[], int n) {
        int sum = 0;
        int leftsum = 0;
        for (int i = 0; i < n; ++i) 
          sum += arr[i];
        for (int i = 0; i < n; ++i) {
            sum -= arr[i];
            if (leftsum == sum) 
               return i;
            leftsum += arr[i];
        }
        return -1;
    }
}


AgileUML: 

class EQUILIBRIUM_INDEX_OF_AN_ARRAY_1 {
  static operation M209( arr : Sequence(int), n : int) : int
  pre: true
  post: true
  activity: (
     var sum : int ; sum := 0 ;
     var leftsum : int ; leftsum := 0 ;
        var i : int ; i := 0 ;
        while i < n do (
          sum := sum+(arr[i+1]) ;
          i := i + 1 ) ; 
        var i : int ; i := 0 ; 
        while i < n do ( 
        (     sum := sum-(arr[i+1]) ; 
     
              if (leftsum = sum) then     return i else skip ; 
    
              leftsum := leftsum+(arr[i+1]) ; 
 )   ; 
           i := i + 1 ) ; 
    return -1 
 );

}

Classes 1/1
Operations 1/3
Variables 5/5
Statements 14/14
Accuracy = 21/23

Consistency = 23/23

Trained LLM: 

class EQUILIBRIUM_INDEX_OF_AN_ARRAY_1 {
  static   operation M209( arr : Sequence(int), n : int) : int
  pre: true
  post: true
  activity: (     var sum : int ; sum := 0 ;
     var leftsum : int ; leftsum := 0 ;
         var i : int ; i := 0 ; while i < n do ( 
     sum := sum+(arr[i+1]) ;  ;     i := i + 1 ) ;
        var i : int ; i := 0 ; while i < n do ( (     sum := sum-(arr[i+1]) ;
     if (leftsum = sum) then      return i else skip ;
     leftsum := leftsum+(arr[i+1]) )  ;     i := i + 1 ) ;
    return -1
 );
}
 <EOF>

Classes 1/1
Operations 3/3
Variables 4/5
Statements 14/14
Accuracy = 22/23

Consistency = 22/23

Untrained LLM:

context EQUILIBRIUM_INDEX_OF_AN_ARRAY_1::M209(arr: Sequence(Integer), n: Integer) : Integer
pre: n > 0 -- The array must have at least one element
post: if result <> -1 then
         -- If an equilibrium index is found, the sum of elements to the left of index i should equal the sum of elements to the right
         arr->subSequence(1, result - 1)->sum() = arr->subSequence(result + 1, n)->sum()
      else
         -- If no equilibrium index is found, the result is -1
         true
      endif

Classes 1/1
Operations 1/3
Variables 3/5
Statements 14/14
Accuracy 19/23
(pre: n <= arr->size() also needed)
Implicit specification, not effective for code generation

Consistency 6/7


Example 4: 

public class NUMBER_SUBSEQUENCES_STRING_DIVISIBLE_N {
static int M516(String str, int n) {
  int len = str.length();
  int dp[][] = new int[len][n];
  dp[0][(str.charAt(0) - '0') % n]++;
  for (int i = 1; i < len; i++) {
    dp[i][(str.charAt(i) - '0') % n]++;
    for (int j = 0; j < n; j++) {
      dp[i][j] += dp[i - 1][j];
      dp[i][(j * 10 + (str.charAt(i) - '0')) % n] += dp[i - 1][j];
    }
  }
  return dp[len - 1][0];
}
}


AgileUML: 

class NUMBER_SUBSEQUENCES_STRING_DIVISIBLE_N {
  static operation M516( str : String, n : int) : int
  pre: true
  post: true
  activity: (     
     var len : int ; len := str->size() ;
     var dp : Sequence(Sequence(int)) ; 
     dp := Integer.subrange(1,len)->collect(Integer.subrange(1,n)->collect(0)) ;
    dp[0+1][(str->at(0+1) - ('0')->char2byte()) mod n+1] := dp[0+1][(str->at(0+1) - ('0')->char2byte()) mod n+1] + 1 ; 
    var i : int ; i := 1 ; 
    while i < len do ( 
    (  dp[i+1][(str->at(i+1) - ('0')->char2byte()) mod n+1] := dp[i+1][(str->at(i+1) - ('0')->char2byte()) mod n+1] + 1 ; 
       var j : int ; j := 0 ; 
       while j < n do ( 
       ( dp[i+1][j+1] := dp[i+1][j+1]+(dp[i - 1+1][j+1]) ; 
     
         dp[i+1][(j * 10 + (str->at(i+1) - ('0')->char2byte())) mod n+1] := dp[i+1][(j * 10 + (str->at(i+1) - ('0')->char2byte())) mod n+1]+(dp[i - 1+1][j+1]) ; 
 )   ;     
         j := j + 1 ) ; 
 )   ;     
        i := i + 1 ) ; 
    return dp[len - 1+1][0+1] 
 );

}

Classes 1/1
Operations 1/3
Variables 6/6
Statements 12/13
Accuracy 20/23

Consistency = 22/23
(missing ->char2byte)

Trained LLM:
 
class NUMBER_SUBSEQUENCES_STRING_DIVISIBLE_N {
  static   operation M516( str : String, n : int) : int
  pre: true
  post: true
  activity: (     var len : int ; len := str->size() ;
     var dp : Sequence(Sequence(int)) ; dp := Integer.subrange(1,len)->collect(Integer.subrange(1,n)->collect(0)) ;
    dp[0+1][(str->at(0+1) - ('0')->char2byte()) mod n+1] := dp[0+1][(str->at(0+1) - ('0')->char2byte()) mod n+1] + 1 ;
        var i : int ; i := 1 ; while i < len do ( (     dp[i+1][(str->at(i+1) - ('0')->char2byte()) mod n+1] := dp[i+1][(str->at(i+1) - ('0')->char2byte()) mod n+1] + 1 ;
         var j : int ; j := 0 ; while j < n do ( (     dp[i+1][j+1] := dp[i+1][j+1]+(dp[i - 1+1][j+1]) ;
     dp[i+1][(j * 10 + (str->at(i+1) - ('0')->char2byte())) mod n+1] := dp[i+1][(j * 10 + (str->at(i+1) - ('0')->char2byte())) mod n+1]+(dp[i - 1+1][j+1]) )  ;     j := j + 1 ) )  ;     i := i + 1 ) ;
    return dp[len - 1+1][0+1]
 );
}
 <EOF>

Classes 1/1
Operations 3/3
Variables 5/6
Statements 12/13
Accuracy 21/23

Consistency = 21/23

Untrained LLM: 

context NUMBER_SUBSEQUENCES_STRING_DIVISIBLE_N::M516(str: String, n: Integer) : Integer
pre: n > 0 and str.size() > 0 and str->forAll(c | c >= '0' and c <= '9')
post: result = 
  let dp: Sequence(Sequence(Integer)) = Sequence{Sequence{0..(n-1) | 0}->including((str.substring(1,1).toInteger() mod n))}
  in
    dp->iterate(i; subsequences: Sequence(Sequence(Integer)) = dp |
      subsequences->including(
        Sequence{0..(n-1) | dp->at(i-1)->at(j) + dp->at(i-1)->at((j * 10 + str.substring(i,i).toInteger()) mod n)}
      )
    )->last()->first()

Classes 1/1
Operations 1/3
Variables 5/6
Statements 0/13
Accuracy = 7/23

Consistency = 5/12
(too complex to express as a simple specification)


Example 5: 

public class SUM_SERIES_0_6_0_06_0_006_0_0006_N_TERMS{
static double ffdsfs(int n){
  return(0.666)*(1-1/Math.pow(10,n));
}
}

AgileUML:

class SUM_SERIES_0_6_0_06_0_006_0_0006_N_TERMS {
  static   operation ffdsfs( n : int) : double
  pre: true
  post: true
  activity: (     return (0.666) * (1 - 1 / 10->pow(n))
 );

}

Classes 1/1
Operations 1/3
Variables 1/1
Statements 1/1
Total accuracy = 4/6

Consistency = 3/3

Trained LLM: 

class SUM_SERIES_0_6_0_06_0_006_0_0006_N_TERMS {
  static   operation ffdsfs( n : int) : double
  pre: true
  post: true
  activity: (     return (0.666) * (1 - 1 / 10->pow(n)) );
}
 <EOF>

Classes 1/1
Operations 3/3
Variables 1/1
Statements 1/1
Total accuracy = 6/6

Consistency = 6/6


Untrained LLM:

-- Context: SUM_SERIES_0_6_0_06_0_006_0_0006_N_TERMS class
context SUM_SERIES_0_6_0_06_0_0006_N_TERMS

-- Operation: ffdsfs(n: Integer): Real
inv:
  let factor: Real = 0.666 in
  factor = 0.666

-- The operation specification in OCL
context SUM_SERIES_0_6_0_06_0_0006_N_TERMS::ffdsfs(n: Integer): Real
pre: n >= 0 -- n must be a non-negative integer
post: 
  result = 0.666 * (1 - 1 / 10^n) -- Formula to calculate the sum of the series up to n terms

Classes 1/1
Operations 1/3
Variables 1/1
Statements 1/1
Accuracy 4/6

Consistency 5/6
(the let factor... is spurious)


Example 6: 

public class TOTAL_NUMBER_OF_NON_DECREASING_NUMBERS_WITH_N_DIGITS_1{
static long aaa(int n){
  int N=10;
  long count=1;
  for(int i=1;i<=n;i++){
    count=(int)count*(N+i-1);
    count=(int)count/i;
  }
  return count;
}
}

AgileUML: 

class TOTAL_NUMBER_OF_NON_DECREASING_NUMBERS_WITH_N_DIGITS_1 {
  static   operation aaa( n : int) : long
  pre: true
  post: true
  activity: (     var N : int ; N := 10 ;
     var count : long ; count := 1 ;
     var i : int ; i := 1 ; 
     while i <= n do ( 
     (  count := count->oclAsType(int) * (N + i - 1) ; 
        count := count->oclAsType(int) / i ; 
 )   ;
        i := i + 1 ) ; 
    return count 
 );

}

Classes 1/1
Operations 1/3
Variables 4/4
Statements 8/8
Accuracy = 14/16

Consistency 13/13


Trained LLM: 

class TOTAL_NUMBER_OF_NON_DECREASING_NUMBERS_WITH_N_DIGITS_1 {
  static   operation aaa( n : int) : long
  pre: true
  post: true
  activity: (     var N : int ; N := 10 ;
     var count : long ; count := 1 ;
         var i : int ; i := 1 ; while i <= n do ( (     count := count->oclAsType(int) * (N + i - 1) ;
     count := count->oclAsType(int) / i )  ;     i := i + 1 ) ;
     return count );
}
 <EOF>

Classes 1/1
Operations 3/3
Variables 4/4
Statements 8/8
Accuracy = 16/16

Consistency 15/15

Untrained LLM:

-- Context: TOTAL_NUMBER_OF_NON_DECREASING_NUMBERS_WITH_N_DIGITS_1 class
context TOTAL_NUMBER_OF_NON_DECREASING_NUMBERS_WITH_N_DIGITS_1

-- Operation: aaa(n: Integer): Long
inv:
  let N: Integer = 10 in
  let count: Long = 1 in
  count = self.aaa(n)

-- The operation specification in OCL
context TOTAL_NUMBER_OF_NON_DECREASING_NUMBERS_WITH_N_DIGITS_1::aaa(n: Integer): Long
pre: n > 0 -- The number of digits (n) must be positive
post:
  result = (Sequence{1..n}->iterate(i; count: Long = 1 | 
             (count * (N + i - 1)) / i)) -- Iterative calculation of count


Classes 1/1
Operations 1/3
Variables 3/4
Statements 4/8
Accuracy = 9/16

Consistency 5/8
(the let N.. is spurious. Conversions to int are missing)


AgileUML
Accuracy = 87/100 = 0.87
Consistency = 85/86 = 0.99
F1 = 0.93


Trained LLM
Overall accuracy = 94/100 (0.94)
Overall consistency = 91/96 (0.95)
F1 = 0.945

Untrained LLM
Overall accuracy = 65/100 (0.65)
Overall consistency = 37/52 (0.71)
F1 = 0.68