node shortest distance from source previous node none none none none none none the adjacency list for the diagram and table is as followsgraph dict(graph[' '{' ' ' ' ' ' graph[' '{' ' ' ' graph[' '{' ' ' ' graph[' '{' ' ' ' ' ' graph[' '{' ' ' ' graph[' '{' ' ' ' the nested dictionary holds the distance and adjacent nodes this table forms the basis for our effort as we try to solve the problem at hand when the algorithm startswe have no idea what the shortest distance from the source (ato any of the nodes is to play it safewe set the values in that column to infinity with the exception of node from the starting nodethe distance covered from node to node is so we can safely use this value as the shortest distance from node to itself no prior nodes have been visited when the algorithm begins we therefore mark the previous node column of node as none in step of the algorithmwe start by examining the adjacent nodes of node to find the shortest distance from node to node bwe need to find the distance from the start node to the previous node of node bwhich happens to be node aand add it to the distance from node to node we do this for other adjacent nodes of awhich are beand using the adjacent node as an examplethe distance from the start node to the previous node is the distance from the previous node to the current node (bis this sum is compared with the data in the shortest distance column of node since is less than infinity()we replace with the smallest of the twowhich is