idm.graph.alg.kosaraju — edu.bard/idm.graph 0.1.1

Kosaraju algorithm implementation

assign clj

(assign graph ordered)

Iterates over the ordered nodes produced by visit to produce a map of pairs of the form [node root-node], where node belongs to the component rooted at root-node. For a graph with no cycles, all entries will be [node node]; i.e., every node belongs to a single-node compoment of which it is the root.

The idea behind this part of the algorithm is that a node is the root of its own component (as encapsulated in the loop variable derived from ordered), unless we have reason to think otherwise. Specifically, if the first time we encounter a node is in the original ordered items, then it is not a predecessor of any node yet processed and is thus a root.

Continuing example from visit; ordered is (:e :d :a :b :c). We start by pairing each item in ordered with itself: ([:e :e] [:d :d] [:a :a] [:b :b] [:c :c])

* node: :e; root: :e; tail: ([:d :d] [:a :a] [:b :b] [:c :c]); components: {}
  - not yet in components, so we prepend predecessors to queue, add to
    components, and recur. :e has no predecessors so queue is unchanged.
* node: :d; root: :d; tail: ([:a :a] [:b :b] [:c :c]); components: {:e :e}
  - not yet in components; add and prepend predecessors (:e) to queue paired
    with :d as their root
* node: :e; root: :d; tail: ([:a :a] [:b :b] [:c :c]); components: {:e :e, :d :d}
  - already in components so simply recur with tail and components
* node: :a; root: :a; tail: ([:b :b] [:c :c]); components: {:e :e, :d :d}
  - add to components and prepend predecessors (:c) to queue paired with :a
* node: :c; root: :a; tail: ([:b :b] [:c :c]); components: {:e :e, :d :d, :a :a}
  - add to components; prepend predecessors (:b) to queue still paired with :a
* node: :b; root: :a; tail: ([:b :b] [:c :c]); components: {:e :e, :d :d, :a :a, :c :a}
  - add to components; prepend predecessors (:a) to queue still paired with :a
* node: :a; root: :a; tail: ([:b :b] [:c :c]); components: {:e :e, :d :d, :a :a, :c :a, :b :a}
  - already present; continue
* node: :b; root: :b; tail: ([:c :c]); components: {:e :e, :d :d, :a :a, :c :a, :b :a}
  - already present; continue
* node: :c; root: :c; tail: (); components: {:e :e, :d :d, :a :a, :c :a, :b :a}
  - already present; continue

And we're done!

{:e :e
 :d :d
 :a :a
 :c :a
 :b :a}

This map contains an entry for each node, where the value is the root node of the component it belongs to. As seen here, several nodes belong to a component rooted in :a, and this indicates a loop.

assign-edges clj

(assign-edges graph ordered)

find-cycle clj

(find-cycle orig-graph edges)

Wraps kosaraju by putting edges into a graph first.

kosaraju clj

(kosaraju graph)

Finds all strongly-connected components in a graph. This is actually not ideal for the use case because we only need one at a time, and the graph will not be the same at each iteration.

https://en.wikipedia.org/wiki/Kosaraju%27s_algorithm

Consider a simple graph, consisting of 5 nodes: :a :b :c :d :e and 5 edges:

  :a -> :b
  :b -> :c
  :c <-> :a
  :d -> :a
  :e -> :d

This contains one loop, :a -> :b -> :c <-> :a. To detect it (and all others), we will first order the nodes via visit, then use that order to produce a component map via assign. Example continued in visit.

visit clj

(visit graph)

Visits all nodes in a graph, producing an ordered sequence used by assign to locate strongly-connected components.

Continuing the example from kosaraju (look at the graph there first): There isn't any requirement of initial node order; suppose we start with (:a :b :c :d :e). * denotes start of visit call.

* node: `:a`; visited: `#{}`; ordered: `()`
  - Not yet visited so recurse on children, namely `(:b :c)`.
  - Note that we mark `:a` as visited for recursion but do not yet add it to
    `ordered`.
  * node: `:b`; visited: `#{:a}`; ordered: `()`
    - Not yet visited so recurse on children, `(:c)`
    * node: `:c`; visited: `#{:a :b}`; ordered: `()`
      - Not yet visited so recurse on chilren, `(:a)`
      * node: `:a`; visited: `#{:a :b :c}`; ordered: `()`
        - Visited already! Return `ordered` unmodified: `()`
      - With recursive step complete, add `:c` to result of recursive step.
        Yields `(:c)`
    - Recursive step complete; add `:b` to result: `(:b :c)`.
  - Because `:a` has two children, feed result from `:b` into second
    recursive call.
  * node: `:c`; visited: #{:a :b :c}`; ordered: `(:b :c)`
    - Visited already! Return `ordered` unmodified: `(:b :c)`
  - With all children visited, now add `:a` to resulting list: `(:a :b :c)`
* node: `:b`; visited: #{:a :b :c}`; ordered: `(:a :b :c)`
  - Visited; return input unmodified
* node: `:c`; visited: #{:a :b :c}`; ordered: `(:a :b :c)`
  - Visited; return input unmodified
* node: `:d`; visited: #{:a :b :c}`; ordered: `(:a :b :c)`
  - Not yet visited; recursive call on children `(:a)`
  * node: `:a`; visited: #{:a :b :c :d}`; ordered: `(:a :b :c)`
    - Visited already; return input unmodified
  - Recursive step complete; add `:d` to output: `(:d :a :b :c)`.
* node: `:e`; visited: #{:a :b :c :d}`; ordered: `(:d :a :b :c)`
  - Not yet visited; recursive call on children `(:d)`
  * node: `:d`; visited: #{:a :b :c :d :e}`; ordered: `(:d :a :b :c)`
    - Visited already; return input unmodified
  - Recursive step complete; add `:e` to output: `(:e :d :a :b :c)`.
- Original list exhausted; result is `(:a :d :a :b :c)`.

For why this is useful, see assign.

visit-edges clj

(visit-edges graph)