(bdequeue node by setting front front (remove the front element of queueand enqueue the neighbours of alsoadd as the orig of its neighbours front queue rear orig \ (cdequeue node by setting front front and enqueue the neighbours of alsoadd as the orig of its neighbours front queue rear orig \ (ddequeue node by setting front front and enqueue the neighbours of alsoadd as the orig of its neighbours note that has two neighbours and since has already been added to the queue and it is not in the ready statewe will not add and only add front queue rear orig \ (edequeue node by setting front front and enqueue the neighbours of alsoadd as the orig of its neighbours note that has two neighbours and since both of them have already been added to the queue and they are not in the ready statewe will not add them again front queue rear orig \ (fdequeue node by setting front front and enqueue the neighbours of alsoadd as the orig of its neighbours note that has two neighbours and since has already been added to the queue and it is not in the ready statewe will not add and add only front queue rear orig \ (gdequeue node by setting front front and enqueue the neighbours of alsoadd as the orig of its neighbours note that has three neighbours fhand front queue rear orig \ since has already been added to the queuewe will only add and as is our final destinationwe stop the execution of this algorithm as soon as it is encountered and added to the queue nowbacktrack from using orig to find the minimum path thuswe have as - - - features of breadth-first search algorithm space complexity in the breadth-first search algorithmall the nodes at particular level must be saved until their child nodes in the next level have been generated the space complexity is therefore proportional to the number of nodes at the deepest level of the graph given graph with branching factor (number of children at each nodeand depth dthe asymptotic space complexity is the number of nodes at the deepest level (bd