Data Structures and Algorithms

It is a dynamically updateable disk based index structure which implements a hashing scheme and grows or shrinks one bucket at a time.

It is a special case of tree where no node of a tree can have a degree of more than two.

It solves the problem of cards sorting counterintuitively by sorting on the least significant digit first.

It expresses the lower bound of the running time of an algorithm.

The graph is called Weighed graph, if information like cost is associated to the traversal of an edge.

It achieves its goal by merging the concepts of a radix search tree and hashing.

It runs linear time when input is drawn from a uniform distribution.

It represents the upper bound and the lower bound of the running time of an algorithm.

Here, we start searching the hash table sequentially from the beginning of the original hash location if a location is occupied, we check the next location.

It is the method of expressing the loose lower bound of the running time of an algorithm.

It is a graph which has more than one edge between the same two vertices.

Graph is said to be sparse if the number of edges are far less than square of modulus of vertex.

It is the function of expressing the upper bound of the running time of an algorithm.

Primary clustering problem can be almost eliminated if we use quadratic probing scheme.

Division into sublist is done through the choice and use of a pivot value, which is a value in the given list so that all values in the list less than the pivot are put in one list and rest in other list.