Optimizing DFS in Data.Graph

`dfs` is the core function in `Data.Graph` that all other algorithms (`topSort`, `scc`, `bcc`, etc) are based on. It takes a `Graph` and generates a `[Tree Vertex]`.

`dfs` makes use of `generate`, `prune` and `chop` to generate a `[Tree Vertex]` and chop it into the returned `[Tree Vertex]`.

Other functions further transform this `[Tree Vertex]`, for example `topSort` flattens the `[Tree Vertex]` into a `[Vertex]`.

These intermediate trees are unnecessary.
* The trees generated by `generate` are immediately chopped into other trees.
* For `topSort`, the trees returned by `dfs` are immediately turned into a list.

There is no reason we need to create these trees in memory.

I propose combining the existing `generate`, `prune`, and `chop` function into a new core function that eliminates the intermediate trees from `generate` and also allows us to choose what to build from the DFS.

```hs
dfsGraph :: (Vertex -> a -> b) -> (b -> a -> a) -> a -> Graph -> [Vertex] -> a
```

Then we can define, for example

```hs
dfs = dfsGraph Node (:) []
topSort = dfsGraph
```

Benchmarks on a random graph with 10,000 vertices and 100,000 edges:

```
dfs: OK (0.90s)
3.51 ms ± 79 μs, 57% less than baseline
topSort: OK (0.47s)
3.60 ms ± 107 μs, 59% less than baseline
```
Other function such as `scc` and `bcc` should also benefit, I've not implemented them yet.

Thoughts? I can clean up my code into a PR if this sounds good.