This problem is a classic graph problem where you need to find the shortest path between two nodes. Here is a step-by-step solution in Python:

1. First, parse the input array to get the nodes and the edges. The number of nodes is given by the first element of the array. The next N elements are the nodes themselves, and the rest of the elements are the edges.

```python
def parse_input(strArr):
num_nodes = int(strArr[0])
nodes = strArr[1:num_nodes+1]
edges = [tuple(edge.split('-')) for edge in strArr[num_nodes+1:]]
return nodes, edges
```

2. Next, create a graph from the nodes and edges. The graph can be represented as a dictionary where the keys are the nodes and the values are lists of nodes that are directly reachable from the key node.

```python
def create_graph(nodes, edges):
graph = {node: [] for node in nodes}
for edge in edges:
graph[edge[0]].append(edge[1])
graph[edge[1]].append(edge[0])
return graph
```

3. Now, use a breadth-first search (BFS) algorithm to find the shortest path from the first node to the last node. BFS is an algorithm for traversing or searching tree or graph data structures. It starts at the tree root (or some arbitrary node of a graph, sometimes referred to as a 'search key') and explores the neighbor nodes at the present depth prior to moving on to nodes at the next depth level.

```python
def shortest_path(graph, start, end):
queue = [(start, [start])]
while queue:
(node, path) = queue.pop(0)
for next_node in graph[node]:
if next_node in path:
continue
elif next_node == end:
return path + [next_node]
else:
queue.append((next_node, path + [next_node]))
return -1
```

4. Finally, put everything together in the `ShortestPath` function.

```python
def ShortestPath(strArr):
nodes, edges = parse_input(strArr)
graph = create_graph(nodes, edges)
path = shortest_path(graph, nodes[0], nodes[-1])
if path == -1:
return -1
else:
return '-'.join(path)
```

This function first parses the input array, then creates a graph, and finally finds the shortest path from the first node to the last node. If a path exists, it returns the path as a string separated by dashes. If no path exists, it returns -1.

Question

This problem is a classic graph problem where you need to find the shortest path between two nodes. Here is a step-by-step solution in Python:

1. First, parse the input array to get the nodes and the edges. The number of nodes is given by the first element of the array. The next N elements are the nodes themselves, and the rest of the elements are the edges.

```python
def parse_input(strArr):
    num_nodes = int(strArr[0])
    nodes = strArr[1:num_nodes+1]
    edges = [tuple(edge.split('-')) for edge in strArr[num_nodes+1:]]
    return nodes, edges
```

2. Next, create a graph from the nodes and edges. The graph can be represented as a dictionary where the keys are the nodes and the values are lists of nodes that are directly reachable from the key node.

```python
def create_graph(nodes, edges):
    graph = {node: [] for node in nodes}
    for edge in edges:
        graph[edge[0]].append(edge[1])
        graph[edge[1]].append(edge[0])
    return graph
```

3. Now, use a breadth-first search (BFS) algorithm to find the shortest path from the first node to the last node. BFS is an algorithm for traversing or searching tree or graph data structures. It starts at the tree root (or some arbitrary node of a graph, sometimes referred to as a 'search key') and explores the neighbor nodes at the present depth prior to moving on to nodes at the next depth level.

```python
def shortest_path(graph, start, end):
    queue = [(start, [start])]
    while queue:
        (node, path) = queue.pop(0)
        for next_node in graph[node]:
            if next_node in path:
                continue
            elif next_node == end:
                return path + [next_node]
            else:
                queue.append((next_node, path + [next_node]))
    return -1
```

4. Finally, put everything together in the `ShortestPath` function.

```python
def ShortestPath(strArr):
    nodes, edges = parse_input(strArr)
    graph = create_graph(nodes, edges)
    path = shortest_path(graph, nodes[0], nodes[-1])
    if path == -1:
        return -1
    else:
        return '-'.join(path)
```

This function first parses the input array, then creates a graph, and finally finds the shortest path from the first node to the last node. If a path exists, it returns the path as a string separated by dashes. If no path exists, it returns -1.

Knowee AI · Accepted Answer