1 // Preliminary Part about Code Similarity  | 
     1 // Core Part 2 about Code Similarity  | 
     2 //========================================  | 
     2 //===================================  | 
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     5 object C2 {  | 
     5 object C2 {  | 
     6   | 
     6   | 
     7 //(1) Complete the clean function below. It should find  | 
     7 // ADD YOUR CODE BELOW  | 
     8 //    all words in a string using the regular expression  | 
     8 //======================  | 
     9 //    \w+  and the library function   | 
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    10 //  | 
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    11 //         some_regex.findAllIn(some_string)  | 
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    12 //  | 
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    13 //    The words should be Returned as a list of strings.  | 
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    14   | 
     9   | 
    15 def clean(s: String) : List[String] =   | 
    10 //(1)  | 
    16   ("""\w+""".r).findAllIn(s).toList | 
    11 def clean(s: String) : List[String] = """(\w+)""".r.findAllIn(s).toList  | 
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    12     | 
    17   | 
    13   | 
    18   | 
    14   | 
    19 //(2) The function occurrences calculates the number of times    | 
    15 //(2)  | 
    20 //    strings occur in a list of strings. These occurrences should   | 
    16 def occurrences(xs: List[String]): Map[String, Int] = { | 
    21 //    be calculated as a Map from strings to integers.  | 
    17     val ls = xs.distinct  | 
    22   | 
    18     val occLs = for (s <- ls) yield (s, xs.count(_.equals(s)))  | 
    23 def occurrences(xs: List[String]): Map[String, Int] =  | 
    19     occLs.toMap  | 
    24   (for (x <- xs.distinct) yield (x, xs.count(_ == x))).toMap  | 
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    25   | 
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    26 //(3) This functions calculates the dot-product of two documents  | 
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    27 //    (list of strings). For this it calculates the occurrence  | 
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    28 //    maps from (2) and then multiplies the corresponding occurrences.   | 
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    29 //    If a string does not occur in a document, the product is zero.  | 
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    30 //    The function finally sums up all products.   | 
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    31   | 
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    32 def prod(lst1: List[String], lst2: List[String]) : Int = { | 
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    33     val words = (lst1 ::: lst2).distinct  | 
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    34     val occs1 = occurrences(lst1)  | 
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    35     val occs2 = occurrences(lst2)  | 
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    36     words.map{ w => occs1.getOrElse(w, 0) * occs2.getOrElse(w, 0) }.sum | 
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    37 }            | 
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    38   | 
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    39 //(4) Complete the functions overlap and similarity. The overlap of  | 
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    40 //    two documents is calculated by the formula given in the assignment  | 
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    41 //    description. The similarity of two strings is given by the overlap  | 
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    42 //    of the cleaned (see (1)) strings.    | 
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    43   | 
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    44 def overlap(lst1: List[String], lst2: List[String]) : Double = { | 
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    45     val m1 = prod(lst1, lst1)  | 
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    46     val m2 = prod(lst2, lst2)   | 
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    47     prod(lst1, lst2).toDouble / (List(m1, m2).max)  | 
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    48 }  | 
    20 }  | 
    49   | 
    21   | 
    50 def similarity(s1: String, s2: String) : Double =  | 
    22   | 
    51   overlap(clean(s1), clean(s2))  | 
    23 //(3)  | 
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    24 def prod(lst1: List[String], lst2: List[String]) : Int = { | 
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    25     val occM1 = occurrences(lst1)  | 
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    26     val occM2 = occurrences(lst2)  | 
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    27     (for (s <- occM1) yield s._2 * occM2.getOrElse(s._1,0)).sum  | 
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    28 }  | 
    52   | 
    29   | 
    53   | 
    30   | 
    54 /*  | 
    31 //(4)  | 
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    32 def overlap(lst1: List[String], lst2: List[String]) : Double = prod(lst1,lst2) / prod(lst1,lst1).max(prod(lst2,lst2))  | 
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    33   | 
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    34 def similarity(s1: String, s2: String) : Double = overlap(clean(s1), clean(s2))  | 
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    35   | 
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    36   | 
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    37   | 
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    38 /* Test cases  | 
    55   | 
    39   | 
    56   | 
    40   | 
    57 val list1 = List("a", "b", "b", "c", "d")  | 
    41 val list1 = List("a", "b", "b", "c", "d")  | 
    58 val list2 = List("d", "b", "d", "b", "d") | 
    42 val list2 = List("d", "b", "d", "b", "d") | 
    59   | 
    43   | 
    79 Australia. Australia has a comparative advantage in the highly  | 
    63 Australia. Australia has a comparative advantage in the highly  | 
    80 competitive tourism industry due to its rich and varied natural  | 
    64 competitive tourism industry due to its rich and varied natural  | 
    81 heritage which ensures Australia's capacity to attract international  | 
    65 heritage which ensures Australia's capacity to attract international  | 
    82 ecotourists."""  | 
    66 ecotourists."""  | 
    83   | 
    67   | 
    84 similarity(orig1, plag1)  | 
    68 similarity(orig1, plag1) // 0.8679245283018868  | 
    85   | 
    69   | 
    86   | 
    70   | 
    87 // Plagiarism examples from   | 
    71 // Plagiarism examples from   | 
    88 // https://www.utc.edu/library/help/tutorials/plagiarism/examples-of-plagiarism.php  | 
    72 // https://www.utc.edu/library/help/tutorials/plagiarism/examples-of-plagiarism.php  | 
    89   | 
    73   | 
   103 usually broken into short-term (acute) and long-term (chronic)  | 
    87 usually broken into short-term (acute) and long-term (chronic)  | 
   104 effects. Both of these types of harm must be addressed in ecosystem  | 
    88 effects. Both of these types of harm must be addressed in ecosystem  | 
   105 recovery: a controversial tactic that is often implemented immediately  | 
    89 recovery: a controversial tactic that is often implemented immediately  | 
   106 following an oil spill."""  | 
    90 following an oil spill."""  | 
   107   | 
    91   | 
   108 overlap(clean(orig2), clean(plag2))  | 
    92 overlap(clean(orig2), clean(plag2))  // 0.728  | 
   109 similarity(orig2, plag2)  | 
    93 similarity(orig2, plag2)             // 0.728  | 
   110   | 
    94   | 
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    95   | 
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    96    | 
   111 // The punchline: everything above 0.6 looks suspicious and   | 
    97 // The punchline: everything above 0.6 looks suspicious and   | 
   112 // should be looked at by staff.  | 
    98 // should be investigated by staff.  | 
   113   | 
    99   | 
   114 */  | 
   100 */  | 
   115   | 
   101   | 
   116   | 
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   117 }  | 
   102 }  |