Cracking the Coding Interview, 4 Edition - 150 Programming Interview Questions and Solutions

Solutions to Chapter 11 | System Design and Memory Limits
this case?
Usually, in BFS, we mark a node as visited by setting a flag visited in its node class. Here, we
don’t want to do that (there could be multiple searches going on at the same time, so it’s bad
to just edit our data). In this case, we could mimic the marking of nodes with a hash table to
lookup a node id and whether or not it’s been visited.
Other Follow-Up Questions:
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In the real world, servers fail. How does this affect you?
»»
How could you take advantage of caching?
»»
Do you search until the end of the graph (infinite)? How do you decide when to give up?
»»
In real life, some people have more friends of friends than others, and are therefore
more likely to make a path between you and someone else. How could you use this data
to pick where you start traversing?
The following code demonstrates our algorithm:
1 public class Server {
2 ArrayList machines = new ArrayList();
3 }
4
5 public class Machine {
6 public ArrayList persons = new ArrayList();
7 public int machineID;
8 }
9
10 public class Person {
11 private ArrayList friends;
12 private int ID;
13 private int machineID;
14 private String info;
15 private Server server = new Server();
16
17 public String getInfo() { return info; }
18 public void setInfo(String info) {
19 this.info = info;
20 }
21
22 public int[] getFriends() {
23 int[] temp = new int[friends.size()];
24 for (int i = 0; i < temp.length; i++) {
25 temp[i] = friends.get(i);
26 }
27 return temp;
28 }
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