Incorporate feedback from PR review

app/assets/javascripts/base.js

@@ -24,7 +24,8 @@ $.fn.scrollTo = function(selector) {
   }, ANIMATION_DURATION);
 };
 
-$.fn.replaceWithPush = function(a) {
+// Same as $.replaceWith, just returns the new element instead of the deleted one
+$.fn.replaceWithAndReturnNewElement = function(a) {
     const $a = $(a);
     this.replaceWith($a);
     return $a;

app/assets/javascripts/channels/la_exercises.js

@@ -31,7 +31,7 @@ $(document).on('turbolinks:load', function() {
             if ($row.length === 0) {
                 $row = $($('#posted_rfcs')[0].insertRow(0));
             }
-            $row = $row.replaceWithPush(data.html);
+            $row = $row.replaceWithAndReturnNewElement(data.html);
             $row.find('time').timeago();
             $row.click(function () {
                 Turbolinks.visit($(this).data("href"));
@@ -236,7 +236,7 @@ $(document).on('turbolinks:load', function() {
 
             $('#no_chart_data').addClass("d-none");
             transitionStacked();
-            // transitionGrouped();
+            // ToDo: Add button to switch using transitionGrouped();
 
             buildDictionary(additional_user_data);
         }

app/models/exercise.rb

@@ -97,93 +97,93 @@ class Exercise < ApplicationRecord
          submissions.user_type,
          score,
          created_at,
-         (created_at - lag(created_at) over (PARTITION BY submissions.user_id, exercise_id
+         (created_at - lag(created_at) over (PARTITION BY submissions.user_type, submissions.user_id, exercise_id
            ORDER BY created_at)) AS working_time
-  FROM submissions
-  WHERE exercise_id = #{exercise_id} AND study_group_id = #{study_group_id} #{additional_filter}),
-        working_time_with_deltas_ignored AS (
-          SELECT user_id,
-                 user_type,
-                 score,
-                 sum(CASE WHEN score IS NOT NULL THEN 1 ELSE 0 END)
-                     over (ORDER BY user_type, user_id, created_at)                 AS change_in_score,
-                 created_at,
-                 CASE WHEN working_time >= #{StatisticsHelper::WORKING_TIME_DELTA_IN_SQL_INTERVAL} THEN '0' ELSE working_time END AS working_time_filtered
-          FROM working_time_between_submissions
-        ),
-        working_times_with_score_expanded AS (
-          SELECT user_id,
-                 user_type,
-                 created_at,
-                 working_time_filtered,
-                 first_value(score)
-                             over (PARTITION BY user_type, user_id, change_in_score ORDER BY created_at ASC) AS corrected_score
-          FROM working_time_with_deltas_ignored
-        ),
-        working_times_with_duplicated_last_row_per_score AS (
-          SELECT *
-          FROM working_times_with_score_expanded
-          UNION ALL
-          -- Duplicate last row per score and make it unique by setting another created_at timestamp.
-          -- In addition, the working time is set to zero in order to prevent getting a wrong time.
-          -- This duplication is needed, as we will shift the scores and working times by one and need to ensure not to loose any information.
-          SELECT DISTINCT ON (user_type, user_id, corrected_score) user_id,
-                                                                   user_type,
-                                                                   created_at + INTERVAL '1us',
-                                                                   '00:00:00' as working_time_filtered,
-                                                                   corrected_score
-          FROM working_times_with_score_expanded
-        ),
-        working_times_with_score_not_null_and_shifted AS (
-          SELECT user_id,
-                 user_type,
-                 coalesce(lag(corrected_score) over (PARTITION BY user_type, user_id ORDER BY created_at ASC),
-                          0) AS shifted_score,
-                 created_at,
-                 working_time_filtered
-          FROM working_times_with_duplicated_last_row_per_score
-        ),
-        working_times_to_be_sorted AS (
-          SELECT user_id,
-                 user_type,
-                 shifted_score                                                          AS score,
-                 MIN(created_at)                                                        AS start_time,
-                 SUM(working_time_filtered)                                             AS working_time,
-                 SUM(SUM(working_time_filtered)) over (PARTITION BY user_type, user_id) AS total_working_time
-          FROM working_times_with_score_not_null_and_shifted
-          GROUP BY user_id, user_type, score
-        ),
-        working_times_with_index AS (
-          SELECT (dense_rank() over (ORDER BY total_working_time, user_type, user_id ASC) - 1) AS index,
-                 user_id,
-                 user_type,
-                 score,
-                 start_time,
-                 working_time,
-                 total_working_time
-          FROM working_times_to_be_sorted)
-        SELECT index,
-           user_id,
-           user_type,
-           name,
-           score,
-           start_time,
-           working_time,
-           total_working_time
-        FROM working_times_with_index
-           JOIN external_users ON user_type = 'ExternalUser' AND user_id = external_users.id
-        UNION ALL
-        SELECT index,
-           user_id,
-           user_type,
-           name,
-           score,
-           start_time,
-           working_time,
-           total_working_time
-        FROM working_times_with_index
-           JOIN internal_users ON user_type = 'InternalUser' AND user_id = internal_users.id
-        ORDER BY index, score ASC LIMIT 200;
+      FROM submissions
+      WHERE exercise_id = #{exercise_id} AND study_group_id = #{study_group_id} #{additional_filter}),
+    working_time_with_deltas_ignored AS (
+      SELECT user_id,
+             user_type,
+             score,
+             sum(CASE WHEN score IS NOT NULL THEN 1 ELSE 0 END)
+                 over (ORDER BY user_type, user_id, created_at ASC)                 AS change_in_score,
+             created_at,
+             CASE WHEN working_time >= #{StatisticsHelper::WORKING_TIME_DELTA_IN_SQL_INTERVAL} THEN '0' ELSE working_time END AS working_time_filtered
+      FROM working_time_between_submissions
+    ),
+    working_times_with_score_expanded AS (
+      SELECT user_id,
+             user_type,
+             created_at,
+             working_time_filtered,
+             first_value(score)
+                         over (PARTITION BY user_type, user_id, change_in_score ORDER BY created_at ASC) AS corrected_score
+      FROM working_time_with_deltas_ignored
+    ),
+    working_times_with_duplicated_last_row_per_score AS (
+      SELECT *
+      FROM working_times_with_score_expanded
+      UNION ALL
+      -- Duplicate last row per user and score and make it unique by setting another created_at timestamp.
+      -- In addition, the working time is set to zero in order to prevent getting a wrong time.
+      -- This duplication is needed, as we will shift the scores and working times by one and need to ensure not to loose any information.
+      SELECT DISTINCT ON (user_type, user_id, corrected_score) user_id,
+                                                               user_type,
+                                                               created_at + INTERVAL '1us',
+                                                               '00:00:00' as working_time_filtered,
+                                                               corrected_score
+      FROM working_times_with_score_expanded
+    ),
+    working_times_with_score_not_null_and_shifted AS (
+      SELECT user_id,
+             user_type,
+             coalesce(lag(corrected_score) over (PARTITION BY user_type, user_id ORDER BY created_at ASC),
+                      0) AS shifted_score,
+             created_at,
+             working_time_filtered
+      FROM working_times_with_duplicated_last_row_per_score
+    ),
+    working_times_to_be_sorted AS (
+      SELECT user_id,
+             user_type,
+             shifted_score                                                          AS score,
+             MIN(created_at)                                                        AS start_time,
+             SUM(working_time_filtered)                                             AS working_time_per_score,
+             SUM(SUM(working_time_filtered)) over (PARTITION BY user_type, user_id) AS total_working_time
+      FROM working_times_with_score_not_null_and_shifted
+      GROUP BY user_id, user_type, score
+    ),
+    working_times_with_index AS (
+      SELECT (dense_rank() over (ORDER BY total_working_time, user_type, user_id ASC) - 1) AS index,
+             user_id,
+             user_type,
+             score,
+             start_time,
+             working_time_per_score,
+             total_working_time
+      FROM working_times_to_be_sorted)
+    SELECT index,
+       user_id,
+       user_type,
+       name,
+       score,
+       start_time,
+       working_time_per_score,
+       total_working_time
+    FROM working_times_with_index
+       JOIN external_users ON user_type = 'ExternalUser' AND user_id = external_users.id
+    UNION ALL
+    SELECT index,
+       user_id,
+       user_type,
+       name,
+       score,
+       start_time,
+       working_time_per_score,
+       total_working_time
+    FROM working_times_with_index
+       JOIN internal_users ON user_type = 'InternalUser' AND user_id = internal_users.id
+    ORDER BY index, score ASC;
     """
   end
 
@@ -210,7 +210,7 @@ class Exercise < ApplicationRecord
       additional_user_data[bucket] ||= []
       additional_user_data[max_bucket + 1] ||= []
 
-      user_progress[bucket][tuple['index']] = tuple["working_time"]
+      user_progress[bucket][tuple['index']] = tuple["working_time_per_score"]
       additional_user_data[bucket][tuple['index']] = {start_time: tuple["start_time"], score: tuple["score"]}
       additional_user_data[max_bucket + 1][tuple['index']] = {id: tuple['user_id'], type: tuple['user_type'], name: tuple['name']}
     end