A binary search algorithm could be applied to find the biggest t for which p is still a corner.

The uniform binary search algorithm looks like this, when implemented in C.

This is equivalent to binary search algorithm to eliminate possible paths which lead to inconsistency.

An example of decrease and conquer algorithm is the binary search algorithm.

If the binary search algorithm is to operate on large arrays, this has two implications:

This algorithm tries to find the maximum where to keep the window at for a long period of time, by using a binary search algorithm.

The binary search algorithm proceeds as follows:

The binary search algorithm can also be expressed iteratively with two index limits that progressively narrow the search range.

NET Framework 2.0 offers static generic versions of the binary search algorithm in its collection base classes.

Another approach would be to use a binary search algorithm which would yield a result comparable in speed to the stencil jumping algorithm.

To search for a given key value, apply a standard binary search algorithm in a binary search tree, ignoring the priorities.

The binary search algorithm is a method of searching a sorted array for a single element by cutting the array in half with each recursive pass.

"A competitor could arguably design around this particular patent by using an oscillator tuning technique that avoided the use of a binary search algorithm," Igoe explained.

For example, a binary search algorithm usually outperforms a brute force sequential search when used for table lookups on sorted lists.

The process is analogous to a binary search algorithm in computer science or successive approximation ADC in analog-to-digital signal conversion.

The path from the root 1 to a number q in the Stern-Brocot tree may be found by a binary search algorithm, which may be expressed in a simple way using mediants.

Uniform binary search is an optimization of the classic binary search algorithm invented by Donald Knuth and given in Knuth's The Art of Computer Programming.

If the location of the first and/or last equal element needs to be determined, this can be done efficiently with a variant of the binary search algorithms which perform only one inequality test per iteration.

In automatic systems this can be done using a binary search algorithm or interpolation search; manual searching may be performed using a roughly similar procedure, though this will often be done unconsciously.

The name "divide and conquer" is sometimes applied also to algorithms that reduce each problem to only one subproblem, such as the binary search algorithm for finding a record in a sorted list (or its analog in numerical computing, the bisection algorithm for root finding).

Take as an example a program that looks up a specific entry in a sorted list of size n. Suppose this program were implemented on Computer A, a state-of-the-art machine, using a linear search algorithm, and on Computer B, a much slower machine, using a binary search algorithm.

Performing a simple table lookup on a un sorted list of 1,000 entries might require perhaps 2,000 machine instructions (on average, assuming uniform distribution of input values), while performing the same lookup on a sorted list using a binary search algorithm might require only about 40 machine instructions, a very considerable saving.

Most algorithms and data structures for searching a dataset are based on the classical binary search algorithm, and generalizations such as the k-d tree or range tree work by interleaving the binary search algorithm over the separate coordinates and treating each spatial coordinate as an independent search constraint.