Khan Academy Infection

The goal of this project is to create a program that emulates an incremental and rolling release model for experimental software. The details and requirements of the project are found here.

Features

• Lists: infections and users are loaded into the program via text files.
• Total Infection: heuristic infects a user and all of its affiliates (both ancestors and offspring).
• Limited Infection: heuristic infects the maximum number of users under a given limit.
• Perfect Limited Infection: heuristic infects an exact number of users if it is possible.
• Simulation: simulator emulates a real-time situation where users are logging in and out of Khan Academy.
• Hierarchical View: program keeps track of the hierarchy of infections and users.
• Written and tested in Python 3.5

Using the Program

To run the main program, navigate to the src folder of the project and open a terminal window. Run with the following command (Python 3 is required):

python main.py

You will then be prompted by the following options, which directly correspond to the features. Select a valid number to continue an action.

[1] Load infections from file.
[2] Load users from file.
[3] Infect a user with a disease (total_infection).
[4] Infect at most a certain amount of users if possible (limited_infection).
[5] Infect exactly a certain amount of users if possible (limited_infection_perfect).
[6] Simulate real-time, user-infection interaction.
[7] Print the infection hierarchy.
[8] Print the user hierarchy and each user's associated infections.
[9] Reset all users and infections to defaults.
[10] Clear all users and infections.
[11] Exit.

Please select an action to perform: 

Simulator

The program can simulate a minute-by-minute timespan, where users are actively interacting with Khan. When a user is online, they have a chance of experiencing instability (called malevolent infections in the program), and the simulator handles these instabilities based on the properties of the infection causing the instability (see Infections). The program will roll back infections on the fly if issues are reported or detected, so users will be (mostly) shielded from these bugs.

Lists

Infections

The format for infections is relatively simple. There is a new infection entry on each line and the indentation of the line determines the hierarchical placement of the entry. The format is as follows:

<Name>(<Severity>, <Contagiousness>)

The severity of an infection is an integer value in the range [0, 100] that determines how critical an infection is to the user experience. During the simulation, if a user runs into an issue with an infection, the severity determines how quickly that infection is rolled back back from other users.

The contagiousness of an infection is an integer value in the range [0, 100] that determines how many users an infection will reach. During the simulation, when a user logs in, contagiousness determines how likely that user will get the infection.

Sample

Infection1(55, 15)
	Infection2(24, 54)
	Infection3(23, 46)
	Infection4(93, 17)
		Infection5(8, 52)
	Infection6(2, 85)
Infection7(78, 77)
	Infection8(66, 55)
	Infection9(61, 73)
		Infection10(8, 36)
		Infection11(60, 99)
Infection12(6, 97)
Infection13(79, 30)
Infection14(82, 95)
	Infection15(30, 5)

Users

The format for users is the same as infections, except that there are no parameters next to each entry. It is just a hierarchical list by tabs.

Sample

User1
	User2
		User3
User4
User5
	User6
	User7
		User8
			User9
				User10
		User11
	User12
User13
User14
User15

Generating Lists

There is also a separate script that auto-generates random hierarchical lists. To run the generator program, navigate to the src folder of the project and open a terminal window. Run with the following command:

python generator.py

You will be prompted with a menu similar to the main program:

[1] Generate random infection file.
[2] Generate random user file.
[3] Exit.