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‎exercises/practice/result-analyzer/.docs/instructions.md‎

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# Instructions
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The first line of the CSV file contains the headings, the other lines contain the results of the participants.
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Each line has the following elements separated by commas: an id, a name, then 10 points for 10 exercises.
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A maximum of 10 points can be achieved in each exercise. A value of -1 means that no solution has been
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submitted.
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The lines of the files can be read by:
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```scala
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val lines = readCSV()
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```
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For the following calculations should be solved using Scala’s collections with their higher-order
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functions. Try to implement each calculation by a single chain of operations.
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## Task 1: Building a list of Results objects
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The first task is to build a list of Results objects from the read lines. Implement a case class Results
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with an id of type Int, as name of type String and an list of points of type List[Int]. Then compute
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the list of Results objects for the participants
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```scala
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val resultList : List[Results] = ???
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```
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## Task 2: Number of solved tasks
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From the list of Results objects, create a map that contains the number of solved exercises for each
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student. An exercise is considered solved if at least 3 points have been achieved.
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## Task 3: Sufficient tasks solved
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A student must solve at least 8 exercises to pass the course. Determine which students have submitted
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enough solutions and which have not enough solutions.
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```scala
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val sufficientSolved : (Set[String], Set[String]) = ...
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```
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_Hint: Use method partition._
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## Task 4: Grading
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Next, the grades should be determined. The grades are calculated based on the points: There must be at least eight solutions with at least 3
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points. If this is the case, the grading is done based on the average of the best eight solutions according
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to the following scheme:
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```
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- [0.0 .. 5.0) : INSUFFICIENT
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- [5.0 .. 6.25) : SUFFICIENT
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- [6.25 .. 7.5) : SATISFACTORY
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- [7.5 .. 8.75) : GOOD
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- [8.75 .. 1.0] : EXCELLENT
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```
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```scala
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val grades: Map[String, Grade] = ...
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```
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## Task 5: Grade statistics
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Compute statistic measurement from the grading. For each grade, compute the number of students with
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that grade:
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```scala
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val nStudentsWithGrade : Map[Grade, Int] = ...
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```
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## Task 6: Number solved per assignment
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For the 10 exercises, compute how many students have solved them (at least 3 points). Result is a list of
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10 numbers, which indicate how many students have solved the exercises:
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```scala
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val nSolvedPerAssnmt : List[(Int, Int)] = ...
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```
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## Task 7: Average points per assignment
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For the 10 exercises, compute the average of the achieved points. Only the submitted exercises (points
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!= -1) should be considered:
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```scala
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val avrgPointsPerAssnmt : List[(Int, Double)] = ...
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```

‎exercises/practice/result-analyzer/.docs/introduction.md‎

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# Processing Results with Collections
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In this assignment, we want to use the Scala collections API for analyzing the results of a programming
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course. The starting point is a CSV file in which the points achieved in 10 programming exercises are
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stored for the course participants:
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ID,Name,1,2,3,4,5,6,7,8,9,10
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1,Alred Maier,10,8,2,7,10,9,7,6,7,2
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2,Fritz Michalik,8,6,5,7,-1,-1,8,6,8,10
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...

‎exercises/practice/result-analyzer/.meta/Example.scala‎

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object ResultsAnalysis {
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}
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‎exercises/practice/result-analyzer/.meta/config.json‎

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{
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"authors": [
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"mrtob"
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],
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"contributors": [
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"mrtob"
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],
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"files": {
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"solution": [
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"src/main/scala/ResultsAnalysis.scala"
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],
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"test": [
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"src/test/scala/ResultsAnalysisTest.scala"
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],
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"example": [
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".meta/Example.scala"
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],
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"invalidator": [
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"build.sbt"
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]
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},
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"blurb": "Analyze the points of students in a class to ´genrate statistics.",
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"source": "Exercism",
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"source_url": ""
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}

‎exercises/practice/result-analyzer/build.sbt‎

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scalaVersion := "3.4.2"
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libraryDependencies += "org.scalatest" %% "scalatest" % "3.2.19" % Test

‎exercises/practice/result-analyzer/project/build.properties‎

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sbt.version=1.10.1

‎exercises/practice/result-analyzer/src/main/scala/ResultsAnalysis.scala‎

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def readCSV(): List[String] = {
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List(
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"ID,Name,1,2,3,4,5,6,7,8,9,10",
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"1,Jane Doe,9,10,9,6,10,9,10,10,10,9",
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"2,John Doe,8,6,5,7,-1,-1,8,6,8,10",
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"3,Jake Doe,10,9,9,-1,5,-1,8,-1,10,9",
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"4,Jill Doe,10,8,2,7,10,9,7,6,7,2",
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)
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}
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case class Results(id: Int, name: String, points: IndexedSeq[Int])
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enum Grade:
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case EXCELLENT, GOOD, SATISFACTORY, SUFFICIENT, INSUFFICIENT
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object ResultsAnalysis {
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def task1(lines: List[String]): List[Results] =
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//TODO: Implement this method
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???
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def task2(resultList: List[Results]): Map[String, Int] =
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//TODO: Implement this method
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???
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def task3(nSolvedPerStnd: Map[String, Int]): (Set[String], Set[String]) =
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//TODO: Implement this method
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???
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def task4(resultList: List[Results]): Map[String, Grade] =
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//TODO: Implement this method
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???
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def task5(resultList: List[Results]): Map[Grade, Int] =
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//TODO: Implement this method
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???
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def task6(resultList: List[Results]): List[(Int, Int)] =
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//TODO: Implement this method
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???
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def task7(resultList: List[Results]): List[(Int, Double)] =
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//TODO: Implement this method
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???
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def main(args: Array[String]): Unit = {
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val lines = readCSV()
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// Task 1
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val resultList: List[Results] = task1(lines)
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// Task 2
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val nSolvedPerStnd = task2(resultList)
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// Task 3
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val sufficientSolved = task3(nSolvedPerStnd)
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// Task 4
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val grades = task4(resultList)
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//Task 5
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val nStudentsWithGrade = task5(resultList)
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//Task 6
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val nSolvedPerAssnmt = task6(resultList)
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//Task 7
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val avrgPointsPerAssnmt = task7(resultList)
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}
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private def computeGrade(points: IndexedSeq[Int]): Grade = {
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if (points.count(p => p >= 3) < 8) then Grade.INSUFFICIENT
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else {
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val avrg = points.sorted.drop(2).sum / 8
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if (avrg < 5.0) then Grade.INSUFFICIENT
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else if (avrg < 6.5) then Grade.SUFFICIENT
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else if (avrg < 8.0) then Grade.SATISFACTORY
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else if (avrg < 9.0) then Grade.GOOD
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else Grade.EXCELLENT
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}
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}
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}

‎exercises/practice/result-analyzer/src/test/scala/ResultsAnalysisTest.scala‎

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import org.scalatest.funsuite.AnyFunSuite
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import org.scalatest.matchers.should.Matchers
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import scala.collection.immutable.HashMap
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/** @version 1.2.0 */
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class ResultsAnalysisTest extends AnyFunSuite with Matchers {
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test("Task 1") {
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val lines = List(
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"ID,Name,1,2,3,4,5,6,7,8,9,10",
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"1,Jane Doe,9,10,9,6,10,9,10,10,10,9",
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"2,John Doe,8,6,5,7,-1,-1,8,6,8,10",
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"3,Jake Doe,10,9,9,-1,5,-1,8,-1,10,9",
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"4,Jill Doe,10,8,2,7,10,9,7,6,7,2",
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)
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val expectedResults = List(
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Results(1, "Jane Doe", IndexedSeq(9, 10, 9, 6, 10, 9, 10, 10, 10, 9)),
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Results(2, "John Doe", IndexedSeq(8, 6, 5, 7, -1, -1, 8, 6, 8, 10)),
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Results(3, "Jake Doe", IndexedSeq(10, 9, 9, -1, 5, -1, 8, -1, 10, 9)),
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Results(4, "Jill Doe", IndexedSeq(10, 8, 2, 7, 10, 9, 7, 6, 7, 2))
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)
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val resultList = ResultsAnalysis.task1(lines)
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resultList shouldEqual expectedResults
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}
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test("Task 2") {
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val results = List(
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Results(1, "Jane Doe", IndexedSeq(9, 10, 9, 6, 10, 9, 10, 10, 10, 9)),
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Results(2, "John Doe", IndexedSeq(8, 6, 5, 7, -1, -1, 8, 6, 8, 10)),
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Results(3, "Jake Doe", IndexedSeq(10, 9, 9, -1, 5, -1, 8, -1, 10, 9)),
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Results(4, "Jill Doe", IndexedSeq(10, 8, 2, 7, 10, 9, 7, 6, 7, 2))
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)
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val expectedResults = Map(
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"Jane Doe" -> 10,
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"John Doe" -> 8,
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"Jake Doe" -> 7,
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"Jill Doe" -> 8
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)
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val resultList = ResultsAnalysis.task2(results)
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resultList shouldEqual expectedResults
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}
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test("Task 3") {
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val results = Map(
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"Jane Doe" -> 10,
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"John Doe" -> 8,
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"Jake Doe" -> 7,
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"Jill Doe" -> 8
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)
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val expectedResults = (Set("Jane Doe", "John Doe", "Jill Doe"), Set("Jake Doe"))
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val resultList = ResultsAnalysis.task3(results)
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resultList shouldEqual expectedResults
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}
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test("Task 4") {
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val results = List(
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Results(1, "Jane Doe", IndexedSeq(9, 10, 9, 6, 10, 9, 10, 10, 10, 9)),
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Results(2, "John Doe", IndexedSeq(8, 6, 5, 7, -1, -1, 8, 6, 8, 10)),
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Results(3, "Jake Doe", IndexedSeq(10, 9, 9, -1, 5, -1, 8, -1, 10, 9)),
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Results(4, "Jill Doe", IndexedSeq(10, 8, 2, 7, 10, 9, 7, 6, 7, 2))
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)
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val expectedResults = Map(
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"Jane Doe" -> Grade.EXCELLENT,
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"John Doe" -> Grade.SATISFACTORY,
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"Jake Doe" -> Grade.INSUFFICIENT,
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"Jill Doe" -> Grade.GOOD
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)
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val resultList = ResultsAnalysis.task4(results)
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resultList shouldEqual expectedResults
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}
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test("Task 5") {
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val results = List(
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Results(1, "Jane Doe", IndexedSeq(9, 10, 9, 6, 10, 9, 10, 10, 10, 9)),
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Results(2, "John Doe", IndexedSeq(8, 6, 5, 7, -1, -1, 8, 6, 8, 10)),
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Results(3, "Jake Doe", IndexedSeq(10, 9, 9, -1, 5, -1, 8, -1, 10, 9)),
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Results(4, "Jill Doe", IndexedSeq(10, 8, 2, 7, 10, 9, 7, 6, 7, 2))
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)
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val expectedResults = HashMap(
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Grade.EXCELLENT -> 1,
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Grade.SATISFACTORY -> 1,
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Grade.INSUFFICIENT -> 1,
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Grade.GOOD -> 1
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)
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val resultList = ResultsAnalysis.task5(results)
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resultList shouldEqual expectedResults
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}
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test("Task 6") {
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val results = List(
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Results(1, "Jane Doe", IndexedSeq(9, 10, 9, 6, 10, 9, 10, 10, 10, 9)),
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Results(2, "John Doe", IndexedSeq(8, 6, 5, 7, -1, -1, 8, 6, 8, 10)),
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Results(3, "Jake Doe", IndexedSeq(10, 9, 9, -1, 5, -1, 8, -1, 10, 9)),
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Results(4, "Jill Doe", IndexedSeq(10, 8, 2, 7, 10, 9, 7, 6, 7, 2))
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)
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val expectedResults = List(
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(1, 4), (2, 4), (3, 3), (4, 3), (5, 3), (6, 2), (7, 4), (8, 3), (9, 4), (10, 3)
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)
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val resultList = ResultsAnalysis.task6(results)
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resultList shouldEqual expectedResults
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}
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test("Task 7"){
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val results = List(
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Results(1, "Jane Doe", IndexedSeq(9, 10, 9, 6, 10, 9, 10, 10, 10, 9)),
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Results(2, "John Doe", IndexedSeq(8, 6, 5, 7, -1, -1, 8, 6, 8, 10)),
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Results(3, "Jake Doe", IndexedSeq(10, 9, 9, -1, 5, -1, 8, -1, 10, 9)),
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Results(4, "Jill Doe", IndexedSeq(10, 8, 2, 7, 10, 9, 7, 6, 7, 2))
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)
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val expectedResults = List(
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(1,9.25), (2,8.25), (3,6.25), (4,6.666666666666667), (5,8.333333333333334), (6,9.0), (7,8.25), (8,7.333333333333333), (9,8.75), (10,7.5)
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)
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val resultList = ResultsAnalysis.task7(results)
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resultList shouldEqual expectedResults
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}
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}

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