core_templates2/docdiff.scala
changeset 396 3ffe978a5664
parent 346 663c2a9108d1
child 428 cdfa6a293453
equal deleted inserted replaced
395:017f621f5835 396:3ffe978a5664
       
     1 // Core Part 2 about Code Similarity
       
     2 //===================================
       
     3 
       
     4 
       
     5 object C2 { 
       
     6 
       
     7 
       
     8 //(1) Complete the clean function below. It should find
       
     9 //    all words in a string using the regular expression
       
    10 //    \w+  and the library function 
       
    11 //
       
    12 //         some_regex.findAllIn(some_string)
       
    13 //
       
    14 //    The words should be Returned as a list of strings.
       
    15 
       
    16 
       
    17 def clean(s: String) : List[String] = ???
       
    18   
       
    19 
       
    20 
       
    21 //(2) The function occurrences calculates the number of times  
       
    22 //    strings occur in a list of strings. These occurrences should 
       
    23 //    be calculated as a Map from strings to integers.
       
    24 
       
    25 
       
    26 def occurrences(xs: List[String]): Map[String, Int] = ???
       
    27 
       
    28 
       
    29 //(3) This functions calculates the dot-product of two documents
       
    30 //    (list of strings). For this it calculates the occurrence
       
    31 //    maps from (2) and then multiplies the corresponding occurrences. 
       
    32 //    If a string does not occur in a document, the product is zero.
       
    33 //    The function finally sums up all products. 
       
    34 
       
    35 
       
    36 def prod(lst1: List[String], lst2: List[String]) : Int = ???
       
    37 
       
    38 
       
    39 //(4) Complete the functions overlap and similarity. The overlap of
       
    40 //    two documents is calculated by the formula given in the assignment
       
    41 //    description. The similarity of two strings is given by the overlap
       
    42 //    of the cleaned strings (see (1)).  
       
    43 
       
    44 
       
    45 def overlap(lst1: List[String], lst2: List[String]) : Double = ???
       
    46 
       
    47 def similarity(s1: String, s2: String) : Double = ???
       
    48 
       
    49 
       
    50 
       
    51 /* Test cases
       
    52 
       
    53 
       
    54 val list1 = List("a", "b", "b", "c", "d") 
       
    55 val list2 = List("d", "b", "d", "b", "d")
       
    56 
       
    57 occurrences(List("a", "b", "b", "c", "d"))   // Map(a -> 1, b -> 2, c -> 1, d -> 1)
       
    58 occurrences(List("d", "b", "d", "b", "d"))   // Map(d -> 3, b -> 2)
       
    59 
       
    60 prod(list1,list2) // 7 
       
    61 
       
    62 overlap(list1, list2)   // 0.5384615384615384
       
    63 overlap(list2, list1)   // 0.5384615384615384
       
    64 overlap(list1, list1)   // 1.0
       
    65 overlap(list2, list2)   // 1.0
       
    66 
       
    67 // Plagiarism examples from 
       
    68 // https://desales.libguides.com/avoidingplagiarism/examples
       
    69 
       
    70 val orig1 = """There is a strong market demand for eco-tourism in
       
    71 Australia. Its rich and diverse natural heritage ensures Australia's
       
    72 capacity to attract international ecotourists and gives Australia a
       
    73 comparative advantage in the highly competitive tourism industry."""
       
    74 
       
    75 val plag1 = """There is a high market demand for eco-tourism in
       
    76 Australia. Australia has a comparative advantage in the highly
       
    77 competitive tourism industry due to its rich and varied natural
       
    78 heritage which ensures Australia's capacity to attract international
       
    79 ecotourists."""
       
    80 
       
    81 similarity(orig1, plag1) // 0.8679245283018868
       
    82 
       
    83 
       
    84 // Plagiarism examples from 
       
    85 // https://www.utc.edu/library/help/tutorials/plagiarism/examples-of-plagiarism.php
       
    86 
       
    87 val orig2 = """No oil spill is entirely benign. Depending on timing and
       
    88 location, even a relatively minor spill can cause significant harm to
       
    89 individual organisms and entire populations. Oil spills can cause
       
    90 impacts over a range of time scales, from days to years, or even
       
    91 decades for certain spills. Impacts are typically divided into acute
       
    92 (short-term) and chronic (long-term) effects. Both types are part of a
       
    93 complicated and often controversial equation that is addressed after
       
    94 an oil spill: ecosystem recovery."""
       
    95 
       
    96 val plag2 = """There is no such thing as a "good" oil spill. If the
       
    97 time and place are just right, even a small oil spill can cause damage
       
    98 to sensitive ecosystems. Further, spills can cause harm days, months,
       
    99 years, or even decades after they occur. Because of this, spills are
       
   100 usually broken into short-term (acute) and long-term (chronic)
       
   101 effects. Both of these types of harm must be addressed in ecosystem
       
   102 recovery: a controversial tactic that is often implemented immediately
       
   103 following an oil spill."""
       
   104 
       
   105 overlap(clean(orig2), clean(plag2))  // 0.728
       
   106 similarity(orig2, plag2)             // 0.728
       
   107 
       
   108 
       
   109  
       
   110 // The punchline: everything above 0.6 looks suspicious and 
       
   111 // should be investigated by staff.
       
   112 
       
   113 */
       
   114 
       
   115 }