Linked from

The 13 pages that link to Binary search, each with the reason it gives.

• AlgorithmBroader topic: It demonstrates how a problem’s structure can reduce the number of required steps.

• Big O notationBroader topic: Its logarithmic running time contrasts sharply with linear search.

• Bisection methodRelated: It shares interval halving, but searches ordered data rather than locating a zero of a continuous function.

• RecursionBroader topic: Its recursive form searches a smaller interval after each comparison.

• Time complexityBroader topic: Its logarithmic running time illustrates the benefit of reducing the search range by half.

• Geometric progressionRelated: Its shrinking search interval forms a geometric progression, explaining logarithmic running time.

• Analysis of algorithmsBroader topic: Its logarithmic search time exemplifies the effect of halving input size.

• Binary search treeRelated: Both methods use ordering to discard candidates, but a tree stores the decisions in its shape.

• Binary treeRelated: Balanced binary search trees echo the repeated partitioning that makes this algorithm efficient.

• Divide-and-conquer algorithmBroader topic: It reduces a problem to one smaller subproblem at each step.

• Master theoremBroader topic: Its recurrence has one half-sized recursive call and constant additional work.

• Red–black treeRelated: Its logarithmic search illustrates the benefit of keeping tree paths short.

• Akra–Bazzi methodRelated: Its recurrence is a simple special case with one recursive subproblem.