diff --git a/src/lib.rs b/src/lib.rs
index 3af0741..fc6a443 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -1,42 +1,127 @@
 /// A trait for graph-like structures, where you can get a node by a unique value and find its neighbors.
 ///
-/// **Node** represents some settled data type
+/// **Node** represents some settled data type. The graph should likely contain `Option<Node>`
+/// elements prepopulated with `None` values. For example `[[None; WIDTH]; HEIGHT]` for a 2D grid.
 ///
 /// **NodeId** represents something that can be used to find an Node inside the graph, such as
 /// position, index, or key to a hashmap. It should allow O(1) access to the Node.
 pub trait GraphLike<Node, NodeId> {
+    /// Number of steps to backtrack after encountering an impossible node.
+    ///
+    /// Used in the default implementation of `full_generation`
+    const BACKTRACK_AMOUNT: usize = 5;
+    /// Maximum number of times we try to retry before making progress. If exceeded, we give up.
+    ///
+    /// Used in the default implementation of `full_generation`
+    const MAX_RETRIES: usize = 5;
+
     fn get_node(&self, id: NodeId) -> Option<&Node>;
-    fn set_node(&mut self, id: NodeId, node: Node);
+    fn set_node(&mut self, id: NodeId, node: Option<Node>);
     fn iter_ids(&self) -> impl Iterator<Item = NodeId>;
     fn iter_neighbor_ids(&self, id: NodeId) -> impl Iterator<Item = NodeId>;
 
-    fn iter_nodes<'a>(&'a self) -> impl Iterator<Item = (NodeId, Option<&'a Node>)> where Node: 'a, NodeId: Copy {
+    fn iter_nodes<'a>(&'a self) -> impl Iterator<Item = (NodeId, Option<&'a Node>)>
+    where
+        Node: 'a,
+        NodeId: Copy,
+    {
         self.iter_ids().map(|id| (id, self.get_node(id)))
     }
-    fn iter_empty(&self) -> impl Iterator<Item = NodeId> where NodeId: Copy {
+    fn iter_empty(&self) -> impl Iterator<Item = NodeId>
+    where
+        NodeId: Copy,
+    {
         self.iter_ids().filter(|id| self.get_node(*id).is_none())
     }
-    fn iter_neighbour_nodes(&self, id: NodeId) -> Vec<(NodeId, Option<&Node>)> where NodeId: Copy {
-        self.iter_neighbor_ids(id).map(|id| (id, self.get_node(id))).collect()
+    fn iter_neighbour_nodes(&self, id: NodeId) -> Vec<(NodeId, Option<&Node>)>
+    where
+        NodeId: Copy,
+    {
+        self.iter_neighbor_ids(id)
+            .map(|id| (id, self.get_node(id)))
+            .collect()
     }
 
-    /// TODO: Replace return type with a result that explains the reason for failure. This could
-    /// help with rollback to recover from impossible generation
-    fn single_step(&mut self, rules: &impl Ruleset<Node, NodeId>) -> Option<NodeId> where NodeId: Copy, Self: Sized {
-        let id = rules.find_lowest_entropy(self)?;
-        let node = rules.choose(self, id).expect("Ruleset::choose should also return Some if Ruleset::entropy returns Some");
-        let empty_ids = self.iter_empty();
-        
-        None
+    fn single_step(
+        &mut self,
+        rules: &impl Ruleset<Node, NodeId>,
+        retry_count: Option<usize>,
+    ) -> Option<NodeId>
+    where
+        NodeId: Copy,
+        Self: Sized,
+    {
+        let id = rules.find_lowest_entropy(self, retry_count)?;
+        let node = rules
+            .choose(self, id, retry_count)
+            .expect("Ruleset::choose should also return Some if Ruleset::entropy returns Some");
+        self.set_node(id, Some(node));
+        Some(id)
+    }
+
+    fn full_generation(&mut self, rules: &impl Ruleset<Node, NodeId>) -> Result<(), ()>
+    where
+        NodeId: Copy,
+        Self: Sized,
+    {
+        // Ordered list of all the nodes that we have generated. Used for backtracking.
+        let mut steps: Vec<NodeId> = vec![];
+        // Number of times we have backtracked from the same point
+        let mut retries: usize = 0;
+        // The biggest number of steps we have gotten se far
+        let mut most_steps = 0;
+        while self.iter_empty().next().is_some() {
+            match self.single_step(rules, Some(retries)) {
+                Some(id) => {
+                    steps.push(id);
+                    if steps.len() > most_steps {
+                        most_steps = steps.len();
+                        retries = 0;
+                    }
+                }
+                None => {
+                    // Backtracking
+                    let reverse_steps =
+                        steps.split_off(steps.len().saturating_sub(Self::BACKTRACK_AMOUNT));
+                    for step in reverse_steps.into_iter().rev() {
+                        self.set_node(step, None);
+                    }
+                    // Keep track of retries
+                    retries += 1;
+                    most_steps = steps.len();
+                    if retries >= Self::MAX_RETRIES {
+                        return Err(());
+                    }
+                }
+            }
+        }
+        Ok(())
     }
 }
 
 pub trait Ruleset<Node, NodeId> {
-    fn entropy(&self, graph: &impl GraphLike<Node, NodeId>, id: NodeId) -> Option<f32> where NodeId: Copy;
-    fn choose(&self, graph: &impl GraphLike<Node, NodeId>, id: NodeId) -> Option<Node> where NodeId: Copy;
+    fn entropy(&self, graph: &impl GraphLike<Node, NodeId>, id: NodeId) -> Option<f32>
+    where
+        NodeId: Copy;
+    fn choose(
+        &self,
+        graph: &impl GraphLike<Node, NodeId>,
+        id: NodeId,
+        _retry_count: Option<usize>,
+    ) -> Option<Node>
+    where
+        NodeId: Copy;
 
-    fn find_lowest_entropy(&self, graph: &impl GraphLike<Node, NodeId>) -> Option<NodeId> where NodeId: Copy {
-        graph.iter_empty()
+    fn find_lowest_entropy(
+        &self,
+        graph: &impl GraphLike<Node, NodeId>,
+        _retry_count: Option<usize>,
+    ) -> Option<NodeId>
+    where
+        NodeId: Copy,
+    {
+        graph
+            .iter_empty()
             .map(|id| (id, self.entropy(graph, id)))
             // NOTE: Option<f32> implements PartialOrd
             // None is considered smaller than any Some value