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A stack is a last in, first out (LIFO) abstract data type and sequential data structure. A stack may have any abstract data type as a component, but is characterized by two fundamental functions, called pop and push. The push operation includes a new item to the top of the stack, or starts the stack if it is empty. If the stack is full and does not have enough space to locate the given item, the stack is then goes to be in an overflow state. The pop operation replaces an item from the top of the stack. A pop either converts previously concealed results, or items in an empty stack, but if the stack is empty then it bond into underflow state. A stack pointer is the register which acquires the value of the stack. The stack pointer usually points to the top value of the stack.
A stack is a limited data structure, because only small values of operations are performed on it. The nature of the push and pop operations also seems that stack elements have a sequential order. Components are removed from the stack in the reverse order to the specific order of their addition: therefore, the lower components are those that have been on the stack the longest.
Red-Black trees have introduced a new property in the binary search tree that means an extra property of color (red, black). However, as these trees grow, in their operations such
Sort the following array of elements using quick sort: 3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5, 8.
Polynomials like 5x 4 + 2x 3 + 7x 2 + 10x - 8 can be represented by using arrays. Arithmetic operations such as addition & multiplication of polynomials are com
We might sometimes seek a tradeoff among space & time complexity. For instance, we may have to select a data structure which requires a lot of storage to reduce the computation tim
Q. State the difference between a grounded header link list and a circular header link list? Ans: A header linked list is a linked list which all the time c
representation of links list in memory
Example 1: Following are Simple sequence of statements Statement 1; Statement 2; ... ... Statement k; The entire time can be found out through adding the times for
bfs and dfs
A telephone directory having n = 10 records and Name field as key. Let us assume that the names are stored in array 'm' i.e. m(0) to m(9) and the search has to be made for name "X"
What is the time complexity of Merge sort and Heap sort algorithms? Time complexity of merge sort is O(N log2 N) Time complexity of heap sort is O(nlog2n)
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