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Depth-first traversal
A depth-first traversal of a tree visit a node and then recursively visits the subtrees of that node. Likewise, depth-first traversal of a graph visits a vertex and then recursively visits all the vertices adjacent to that node. The catch is that the graph may having cycles, but the traversal must visit each vertex at most once. The solution to the problem is to keep track of the nodes that have been visited, so that the traversal does not undergo the fate of infinite recursion.
Run time complexity of an algorithm is depend on
Worst Case: For running time, Worst case running time is an upper bound with any input. This guarantees that, irrespective of the type of input, the algorithm will not take any lo
Define tractable and intractable problems Problems that can be solved in polynomial time are known as tractable problems, problems that cannot be solved in polynomial time are
Q. How can we free the memory by using Boundary tag method in the context of Dynamic memory management?
State about the pre- and post conditions Programmers can easily document other pre- and post conditions and class invariants, though, and insert code to check most value preco
Records are mapped onto a computer store by simply juxtaposing their elements. The address of a component (field) r relative to the origin address of the record r is named the fiel
A LGORITHM (Deletion of an element from the linked list) Step 1 Begin Step 2 if the list is empty, then element cannot be deleted Step 3 else, if the element to be del
Like general tree, binary trees are implemented through linked lists. A typical node in a Binary tree has a structure as follows struct NODE { struct NODE *leftchild; i
If a node in a binary tree is not containing left or right child or it is a leaf node then that absence of child node can be represented by the null pointers. The space engaged by
B i n a ry Search Algorithm is given as follows 1. if (low > high) 2. return (-1) 3. mid = (low +high)/2; 4. if ( X = = a [mid]) 5. return (mid); 6.
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