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The main difference is that depth-first uses a stack while breadth-first uses a queue.

To illustrate, imagine a binary tree where every node has up to two child nodes and some data. We begin at the root in both cases. With breadth-first, we enqueue the root. We then begin an iterative process. First, we dequeue a node. If the node contains the data being sought then we're done. Otherwise we enqueue the node's immediate children. If the queue is empty, the data being sought does not exist and we're done. Otherwise we begin a new iteration.

With depth first we do the same thing except we stack the nodes (push and pop rather than enqueue and dequeue). Queues are a FIFO structure (first in, first out) while stacks are LIFO (last in, first out). This dramatically alters the sequence in which nodes are examined. Breadth-first examines nodes in sequence, row by row, whereas depth-first examines the depths of the left hand side of each node before examining the depths of the right hand side of each node.

Depth-first is ideally suited to brute force backtracking algorithms (particularly NP-complete problems) as well as for rapidly building sorted lists from unsorted sequential data. Breadth-first search is better suited to creating diagrams from binary trees because a single pass can determine the number of levels and the maximum width required to display the tree, while a second pass can build the diagram one row at a time (typical breadth-first implementations will maintain the width and height as internal members to avoid recalculating them).

Because depth-first employs a stack, implementations often make use of recursion rather than iteration, thus taking advantage of the call stack to provide the necessary backtracking. However, an iterative approach is usually more efficient, particularly if the tree depth exceeds the compiler's ability to inline expand the recursions.

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