// Preliminary Part about Code Similarity

//========================================

object CW7a { 

//(1) Complete the clean function below. It should find

//    all words in a string using the regular expression

//    \w+  and the library function 

//

//         some_regex.findAllIn(some_string)

//

//    The words should be Returned as a list of strings.

def clean(s: String) : List[String] = {

    val regex = """\w+""".r;

    val list_of_words = s.split(" ").toList

    for(word <- list_of_words;

        actual_word <- divide_string_where_different(word, regex.findAllIn(word).mkString, 0)) yield actual_word

}

/*

    A secondary function that takes as parameters @param original which is the original word, @param returned which is thea word after the process of removing 

    some characters not allowed by a regular expression, and @param i which is the index where to start compare the characters of the two words.

    It @return a List of strings which represents all the substrings of returned which were previously divided by characters not allowed by the regular expression applied on it.

*/

def divide_string_where_different(original: String, returned: String, i : Int): List[String] ={

    val max_i = original.length -1

    if(original(i) != returned(i)) returned.substring(0, i)::divide_string_where_different(original.substring(i+1), returned.substring(i), 0).filter(_.nonEmpty)

    else if (i == max_i) List(returned)

    else divide_string_where_different(original,returned, i +1)

}

//(2) The function occurrences calculates the number of times  

//    strings occur in a list of strings. These occurrences should 

//    be calculated as a Map from strings to integers.

def occurrences(xs: List[String]): Map[String, Int] = {

    val lst = xs.distinct

    val word_pairs = (for (word <- lst) yield (word, xs.count(_==word))).toList

    word_pairs.toMap

}

//(3) This functions calculates the dot-product of two documents

//    (list of strings). For this it calculates the occurrence

//    maps from (2) and then multiplies the corresponding occurrences. 

//    If a string does not occur in a document, the product is zero.

//    The function finally sums up all products. 

def prod(lst1: List[String], lst2: List[String]) : Int = {

    val map1 = occurrences(lst1)

    val map2 = occurrences(lst2)

    print(s"map1 is $map1 \n and map2 is $map2")

    val pairs = (for(pair1 <- map1 if(map2.get(pair1._1) != None)) yield (pair1._2, map2.get(pair1._1).get)).toList

    print(s"\n pairs are $pairs")

    val products = (for(pair <- pairs) yield pair._1 * pair._2).toList

    products.sum

}

//(4) Complete the functions overlap and similarity. The overlap of

//    two documents is calculated by the formula given in the assignment

//    description. The similarity of two strings is given by the overlap

//    of the cleaned strings (see (1)).  

//def overlap(lst1: List[String], lst2: List[String]) : Double = ...

//def similarity(s1: String, s2: String) : Double = ...

/* Test cases

val list1 = List("a", "b", "b", "c", "d") 

val list2 = List("d", "b", "d", "b", "d")

occurrences(List("a", "b", "b", "c", "d"))   // Map(a -> 1, b -> 2, c -> 1, d -> 1)

occurrences(List("d", "b", "d", "b", "d"))   // Map(d -> 3, b -> 2)

prod(list1,list2) // 7 

prod(list1,list1)

prod(list2,list2)

overlap(list1, list2)   // 0.5384615384615384

overlap(list2, list1)   // 0.5384615384615384

overlap(list1, list1)   // 1.0

overlap(list2, list2)   // 1.0

// Plagiarism examples from 

// https://desales.libguides.com/avoidingplagiarism/examples

val orig1 = """There is a strong market demand for eco-tourism in

Australia. Its rich and diverse natural heritage ensures Australia's

capacity to attract international ecotourists and gives Australia a

comparative advantage in the highly competitive tourism industry."""

val plag1 = """There is a high market demand for eco-tourism in

Australia. Australia has a comparative advantage in the highly

competitive tourism industry due to its rich and varied natural

heritage which ensures Australia's capacity to attract international

ecotourists."""

similarity(orig1, plag1) // 0.8679245283018868

// Plagiarism examples from 

// https://www.utc.edu/library/help/tutorials/plagiarism/examples-of-plagiarism.php

val orig2 = """No oil spill is entirely benign. Depending on timing and

location, even a relatively minor spill can cause significant harm to

individual organisms and entire populations. Oil spills can cause

impacts over a range of time scales, from days to years, or even

decades for certain spills. Impacts are typically divided into acute

(short-term) and chronic (long-term) effects. Both types are part of a

complicated and often controversial equation that is addressed after

an oil spill: ecosystem recovery."""

val plag2 = """There is no such thing as a "good" oil spill. If the

time and place are just right, even a small oil spill can cause damage

to sensitive ecosystems. Further, spills can cause harm days, months,

years, or even decades after they occur. Because of this, spills are

usually broken into short-term (acute) and long-term (chronic)

effects. Both of these types of harm must be addressed in ecosystem

recovery: a controversial tactic that is often implemented immediately

following an oil spill."""

overlap(clean(orig2), clean(plag2))  // 0.728

similarity(orig2, plag2)             // 0.728

// The punchline: everything above 0.6 looks suspicious and 

// should be investigated by staff.

*/

}