►Fundamentals II
Introduction to Class-based Program Design
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►Lab 6: Working with Cyclic Data
On this page:
Movie costars
Game of telephone
Discussion
8.14
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Lab 6: Working with Cyclic Data🔗

Goals: The goals of this lab is are learn how to design and use circularly referential data.

Movie costars🔗

As you all know, the Fundies Choice Awards are the most coveted awards in the world of Fundieswood. Coincidentally, they provide us a great opportunity to examine actors and their network of costars. We’ll simplify everything about acting and Fundieswood away, and simply claim that an actor is identified by their name and their list of other actors who were in movies with them. By definition, if one actor costarred in a movie with someone else, then that second actor costarred in the same movie with the first, so we immediately get cyclic data.

Your starter code for this problem is as follows. (NOTE: We’re using non-generic lists in the lab deliberately, so we can add whatever helper methods we need. Really, these lists are being used as part of a graph, and so they might deserve to have some special-purpose methods.)

// represents a Actor with a user name and a list of costars class Actor {
String username;
ILoActor costars;
 
Actor(String username) {
this.username = username;
this.costars = new MtLoActor();
}
 
// Methods will be given below }
 
// represents a list of Actor's costars interface ILoActor {
}
 
// represents a list of Actor's costars class ConsLoActor implements ILoActor {
Actor first;
ILoActor rest;
 
ConsLoActor(Actor first, ILoActor rest) {
this.first = first;
this.rest = rest;
}
}
 
// represents an empty list of Actor's costars class MtLoActor implements ILoActor {
MtLoActor() {}
}

Suppose that an actor wins a Fundies Choice Award, and wants to invite their costars to the afterparty to celebrate. This being Fundieswood, of course those guests will invite everyone they know as well, who will in turn invite their costars as well..., eventually inviting everyone that can be reached through this network of costars.

We call those on the actor’s costar list the direct costars and the others that will also be invited to the party the indirect costars. (Note: some people technically qualify as both direct and indirect costars; find an example of such a pair in the examples above.) We call the set of direct and indirect costars the extended costars of a actor.

Now we would like to ask some pretty common questions. For each question design the method that will find the answer. As always, follow the Design Recipe! The purpose/effect statements and the headers for the methods are already given:

HINT: some of these methods will benefit greatly from designing a helper method first, that can be reused to help solve more than one of the questions above. You are encouraged to make a work-list for each problem, to figure out what the high-level steps are first, before diving into writing code without a plan.

Challenge: as everyone knows, the main purpose of examining costars is to play "Six degrees of Kevin Bacon". Design a new method to compute the length of the shortest path from one actor to another. (It’s a variant on hasExtendedCostar...)

Game of telephone🔗

Kids often played a game of telephone, where they sat in a circle and one person whispers a secret message to the next person, who whispers whatever they heard to the next person, and so on, until the last person in the circle announces whatever final message they received...which is often hilariously garbled from the original message.

Now that they’re older (and coincidentally all taking Fundies 2 together) they’ve decided to see how often they can “win” at the game, to see how likely they can convey a message without garbling. So:

The likelihood of person A being understood by person B is therefore the product of person A’s diction with person B’s hearing.

By the rules of the game, each Person will only ever whisper their message to their buddies. Your task is to compute the maximum likelihood that person X can convey a message correctly to person Y.

For example, let’s say:

  • person A has 0.95 diction, and 0.8 hearing, and is buddies with B and C

  • person B has 0.85 diction, and 0.99 hearing, and is buddies with D

  • person C has 0.95 diction, and 0.9 hearing, and is buddies with D

  • person D has 1.0 diction, and 0.95 hearing.

  • no one is friends with person E

Then:

  • The total likelihood of A getting a message to D by way of B is (0.95*0.99)*(0.85*0.95) = 0.759

  • The total likelihood of A getting a message to D by way of C is (0.95*0.95)*(0.9*0.95) = 0.772

So the maximum likelihood is 0.772, by way of person C.

To begin with, you should not compute the actual path the message needs to take, but just produce the maximum likelihood that the message will be received correctly.

Once you have completed that method, you should design another that does produce the path of maximum likelihood.

Discussion🔗

The Fundieswood afterparty methods earlier, and the game of telephone problem above, form two common styles of problem encountered while processing cyclic graphs. The hint in the first problem suggests that there might be some common abstraction you might use to help solve those first tasks. The telephone problem has a similar feel. Brainstorm a little bit: if you had to compare the kinds of computation needed in these problems to a list-processing function, which would it be most like: map, foldr, foldl, filter...? Make some suggestions for what an appropriate abstraction might be for these graph-processing problems.

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