Graph Search Algorithms

Title Page Breadth-First Search Depth-First Search Example BFS/DFS Comparison Exploiting Similarity GraphSearcher.java Example Again
Below is an ExampleGraphTest class that tests the ExampleGraph class.

It runs breadth-first and depth-first searches on the graph. If you have not yet started the Graph Search and Creation module, that's OK. It's enough to know that a side effect of these searches is the linking of vertices through their predecessor fields.

These links can be used to access a resulting predecessor tree and construct solutions to problems.

BFS Approach BFS Advantage BFS Products Role of a Queue BFS Trace BFS Algorithm BFS Runtime BFS Memory
k = 1 k = 2 k = 3 k = 4
Distance Predecessors
Remove S Remove W Remove R Remove T Remove X Remove V Remove U Remove Y
Pseudocode
d = 1 d = 2 d = 3 In General Exponential Intractable
DFS Approach Role of a Stack DFS Algorithm DFS Runtime DFS Memory
k = 1 k = 2 k = 3 Non-optimality
Pseudocode
d = 1 d = 2 d = 3 In General Linear
Maze 1 Maze 2
Consider the maze application below. It shows the problem solver with a solving capability and a choice of BFS or DFS.

BFS DFS
A breadth-first search of maze 1 finds an optimal path of 28 moves.

A depth-first search of maze 1 finds a sub-optimal path of 112 moves.

Here is another maze problem, with barriers.

BFS DFS
A breadth-first search of maze 2 finds an optimal path of 26 moves.

A depth-first search of maze 2 finds a sub-optimal path of 104 moves.

Double-Ended Queue Generic Search