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codeocean/lib/tasks/detect_exercise_anomalies.rake

166 lines
7.0 KiB
Ruby

include Rails.application.routes.url_helpers
namespace :detect_exercise_anomalies do
# uncomment for debug logging:
# logger = Logger.new(STDOUT)
# logger.level = Logger::DEBUG
# Rails.logger = logger
# These factors determine if an exercise is an anomaly, given the average working time (avg):
# (avg * MIN_TIME_FACTOR) <= working_time <= (avg * MAX_TIME_FACTOR)
MIN_TIME_FACTOR = 0.1
MAX_TIME_FACTOR = 2
# Determines how many users are picked from the best/average/worst performers of each anomaly for feedback
NUMBER_OF_USERS_PER_CLASS = 10
# Determines margin below which user working times will be considered data errors (e.g. copy/paste solutions)
MIN_USER_WORKING_TIME = 0.0
# Cache exercise working times, because queries are expensive and values do not change between collections
WORKING_TIME_CACHE = {}
AVERAGE_WORKING_TIME_CACHE = {}
task :with_at_least, [:number_of_exercises, :number_of_solutions] => :environment do |task, args|
number_of_exercises = args[:number_of_exercises]
number_of_solutions = args[:number_of_solutions]
puts "Searching for exercise collections with at least #{number_of_exercises} exercises and #{number_of_solutions} users."
# Get all exercise collections that have at least the specified amount of exercises and at least the specified
# number of submissions AND are flagged for anomaly detection
collections = get_collections(number_of_exercises, number_of_solutions)
puts "Found #{collections.length}."
collections.each do |collection|
puts "\t- #{collection}"
anomalies = find_anomalies(collection)
if anomalies.length > 0 and not collection.user.nil?
notify_collection_author(collection, anomalies)
notify_users(collection, anomalies)
reset_anomaly_detection_flag(collection)
end
end
puts 'Done.'
end
def get_collections(number_of_exercises, number_of_solutions)
ExerciseCollection
.where(:use_anomaly_detection => true)
.joins("join exercise_collections_exercises ece on exercise_collections.id = ece.exercise_collection_id
join
(select e.id
from exercises e
join submissions s on s.exercise_id = e.id
group by e.id
having count(s.user_id) > #{ExerciseCollection.sanitize(number_of_solutions)}
) as exercises_with_submissions on exercises_with_submissions.id = ece.exercise_id")
.group('exercise_collections.id')
.having('count(exercises_with_submissions.id) > ?', number_of_exercises)
end
def find_anomalies(collection)
working_times = {}
collection.exercises.each do |exercise|
puts "\t\t> #{exercise.title}"
working_times[exercise.id] = get_average_working_time(exercise)
end
average = working_times.values.reduce(:+) / working_times.size
working_times.select do |exercise_id, working_time|
working_time > average * MAX_TIME_FACTOR or working_time < average * MIN_TIME_FACTOR
end
end
def time_to_f(timestamp)
unless timestamp.nil?
timestamp = timestamp.split(':')
return timestamp[0].to_i * 60 * 60 + timestamp[1].to_i * 60 + timestamp[2].to_f
end
nil
end
def get_average_working_time(exercise)
unless AVERAGE_WORKING_TIME_CACHE.key?(exercise.id)
seconds = time_to_f exercise.average_working_time
AVERAGE_WORKING_TIME_CACHE[exercise.id] = seconds
end
AVERAGE_WORKING_TIME_CACHE[exercise.id]
end
def get_user_working_times(exercise)
unless WORKING_TIME_CACHE.key?(exercise.id)
exercise.retrieve_working_time_statistics
WORKING_TIME_CACHE[exercise.id] = exercise.working_time_statistics
end
WORKING_TIME_CACHE[exercise.id]
end
def notify_collection_author(collection, anomalies)
puts "\t\tSending E-Mail to author (#{collection.user.displayname} <#{collection.user.email}>)..."
UserMailer.exercise_anomaly_detected(collection, anomalies).deliver_now
end
def notify_users(collection, anomalies)
by_id_and_type = proc { |u| {user_id: u[:user_id], user_type: u[:user_type]} }
puts "\t\tSending E-Mails to best and worst performing users of each anomaly..."
anomalies.each do |exercise_id, average_working_time|
puts "\t\tAnomaly in exercise #{exercise_id} (avg: #{average_working_time} seconds):"
exercise = Exercise.find(exercise_id)
users_to_notify = []
users = {}
[:performers_by_time, :performers_by_score].each do |method|
# merge users found by multiple methods returning a hash {best: [], worst: []}
users = users.merge(send(method, exercise, NUMBER_OF_USERS_PER_CLASS)) {|key, this, other| this + other}
end
# write reasons for feedback emails to db
users.keys.each do |key|
segment = users[key].uniq &by_id_and_type
users_to_notify += segment
segment.each do |user|
reason = "{\"segment\": \"#{key.to_s}\", \"feature\": \"#{user[:reason]}\", value: \"#{user[:value]}\"}"
AnomalyNotification.create(user_id: user[:user_id], user_type: user[:user_type],
exercise: exercise, exercise_collection: collection, reason: reason)
end
end
users_to_notify.uniq! &by_id_and_type
users_to_notify.each do |u|
user = u[:user_type] == InternalUser.name ? InternalUser.find(u[:user_id]) : ExternalUser.find(u[:user_id])
host = CodeOcean::Application.config.action_mailer.default_url_options[:host]
feedback_link = url_for(action: :new, controller: :user_exercise_feedbacks, exercise_id: exercise.id, host: host)
UserMailer.exercise_anomaly_needs_feedback(user, exercise, feedback_link).deliver
end
puts "\t\tAsked #{users_to_notify.size} users for feedback."
end
end
def performers_by_score(exercise, n)
submissions = exercise.last_submission_per_user.where('score is not null').order(score: :desc)
map_block = proc {|item| {user_id: item.user_id, user_type: item.user_type, value: item.score, reason: 'score'}}
best_performers = submissions.first(n).to_a.map &map_block
worst_performers = submissions.last(n).to_a.map &map_block
return {:best => best_performers, :worst => worst_performers}
end
def performers_by_time(exercise, n)
working_times = get_user_working_times(exercise).values.map do |item|
{user_id: item['user_id'], user_type: item['user_type'], score: item['score'].to_f,
value: time_to_f(item['working_time']), reason: 'time'}
end
avg_score = exercise.average_score
working_times.reject! {|item| item[:value].nil? or item[:value] <= MIN_USER_WORKING_TIME or item[:score] < avg_score}
working_times.sort_by! {|item| item[:value]}
return {:best => working_times.first(n), :worst => working_times.last(n)}
end
def reset_anomaly_detection_flag(collection)
puts "\t\tResetting flag..."
collection.use_anomaly_detection = false
collection.save!
end
end