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This Job was made to control automatically the way how to the candidate progresses, taking in count the deviation, structure, complexity, and steps.
Every candidate in the repository is assigned to a policy. Depending on your policy, you will be allowed to solve programming challenges in certain languages, or hacking challenges from certain websites.
There are different types of policies, for instance
only-hack and so on.
It is therefore very important that before you start solving challenges you check which policy has been assigned to you.
The policy is configured in the
data.yaml file within the
folder of the repository.
Following our own rules we see if your deviation always tends to 0, for that you always should make 1 challenge per scope before starting a new cycle, your deviation is evaluated based on the policy and which scopes are active.
This field is composed of 2 parameters, active and list.
Active: This says if the policy limits the sites to the sites in the list.
List: This is the list for the sites that the policy allows to make the challenges.
This field is present in all scopes and we can limit the sites where the trainees work, if this is active our trainee only can make challenges in the sites listed in that field.
This field is only for Code challenges and has 2 parameters, active and list.
Active: This says if the policy limits the langs to the languages in the list.
List: This is the list for the languages that the policy allows to make the challenges.
This helps to choose the language that we want our trainees to use.
This field is only for Code challenges and has 5 parameters, active, min, goal, min_step, and max_step.
Active: This says if the policy evaluates the complexity.
Min: Says the minimum complexity we can accept in the cycles.
Goal: This says what is the expected complexity we want our trainee to reach with the cycles.
Min_step: This is the minimum step that you must reach when uploading a new solution, for example:min_step: 2your previous complexity: 3your minimum expected complexity: min_step + previous_complexityminimum_expected_complexity: 5
Knowing this our trainee must surpass the minimum_expected_complexity.
Max_step: This is the maximum step that you are allowed to reach when uploading a new solution, for example:max_step: 3your previous complexity: 3your maximum expected complexity: max_step + previous_complexitymaximum_expected_complexity: 6
Knowing this our trainee shouldn’t surpass the maximum_expected_complexity.