binary trees be moved to another node where it can be legally placedand the value displaced by will have to be movedand so on until new leaf node is created for the last value displaced instead of starting from the top and searching for node in the tree where the new value can be properly placedwe can start at the bottom and work our way up this involves several stepswhich we outline using figure firstwe create new node and fill it with the new value as shown in part (athe node is then attached as leaf node at the only spot in the tree where the heap shape property can be maintained (part ( )remembera heap is complete tree and in such treethe leaf nodes on the lowest level must be filled from left to right as you will noticethe heap order property has been violated since the parent of node is smaller but in max-heap it is supposed to be larger (acreate new node for (blink the node as the last child (csift-upswap and (dsift-upswap and figure the steps to insert value into the heap to restore the heap order propertythe new value has to move up along the path in reverse order from the root to the insertion point until node is found where it can be positioned properly this operation is known as sift-up it can also be known as an up-heapbubble-uppercolate-upor heapify-upamong others the sift-up operation compares the new value in the new node to the value in its parent node since its parent is smallerwe know it belongs above the parent and the two values are swappedas shown in figure (cvalue is then compared to the value in its new parent node againwe find the parent