diff --git a/packages/graph/package.json b/packages/graph/package.json
index fa4f4d8..54775f4 100644
--- a/packages/graph/package.json
+++ b/packages/graph/package.json
@@ -1,6 +1,6 @@
 {
   "name": "@antv/algorithm",
-  "version": "0.1.11",
+  "version": "0.1.13",
   "description": "graph algorithm",
   "keywords": [
     "graph",
diff --git a/packages/graph/src/gSpan/gSpan.ts b/packages/graph/src/gSpan/gSpan.ts
index b67e258..6e68cd8 100644
--- a/packages/graph/src/gSpan/gSpan.ts
+++ b/packages/graph/src/gSpan/gSpan.ts
@@ -112,11 +112,9 @@ class DFScode {
       const toNodeId = dfsEdge.toNode;
       const { nodeLabel1, edgeLabel, nodeLabel2 } = dfsEdge.nodeEdgeNodeLabel;
 
-      if (nodeLabel1 !== VACANT_NODE_LABEL)
-        graph.addNode(fromNodeId, nodeLabel1);
+      if (nodeLabel1 !== VACANT_NODE_LABEL) graph.addNode(fromNodeId, nodeLabel1);
       if (nodeLabel2 !== VACANT_NODE_LABEL) graph.addNode(toNodeId, nodeLabel2);
-
-      graph.addEdge(undefined, fromNodeId, toNodeId, edgeLabel);
+      if (nodeLabel1 !== VACANT_NODE_LABEL && nodeLabel2 !== nodeLabel1)  graph.addEdge(undefined, fromNodeId, toNodeId, edgeLabel);
     });
     return graph;
   }
@@ -429,6 +427,7 @@ class GSpan {
 
     // 比较 root 中每一项的 nodeEdgeNodeLabel 大小，按照 nodeLabel1、edgeLabe、nodeLabel2 的顺序比较
     let minLabel = this.findMinLabel(root); // line 419
+    if (!minLabel) return;
     dfsCodeMin.dfsEdgeList.push(
       new DFSedge(
         0,
diff --git a/packages/graph/src/gaddi.ts b/packages/graph/src/gaddi.ts
index 9d147cf..586c8fb 100644
--- a/packages/graph/src/gaddi.ts
+++ b/packages/graph/src/gaddi.ts
@@ -204,6 +204,7 @@ const getMatchedCount = (graph, structure, nodeLabelProp, edgeLabelProp) => {
     nodeMap[node.id] = node;
   });
   let count = 0;
+  if (!structure?.edges?.length || structure?.nodes?.length < 2) return 0;
   graph.edges.forEach(e => {
     const sourceLabel = nodeMap[e.source][nodeLabelProp];
     const targetLabel = nodeMap[e.target][nodeLabelProp];
@@ -540,7 +541,6 @@ const GADDI = (
   // );
   // 1.2. 生成上面节点对的相应相交邻居诱导子图。格式为 {'beginNodeIdx-endNodeIdx': {nodes: [], edges: []}}
   let intGMap = getIntersectNeighborInducedGraph(nodePairsMap, kNeighborUnits, graphData);
-
   // 1.3. 使用 gSpan 算法（frequent graph mining）计算 ISIntG 的前 10 个频率最高的子结构（3-4条边）
   const top = 10,
     minSupport = 1,
@@ -797,7 +797,6 @@ const GADDI = (
       }
     }
 
-
       // prune3: 若该邻居点到 candidate 的 NDS 距离比和它有相同 label 的节点到 beginPNode 的最小 NDS 距离小，移除这个点
       const ndsToCandidate = ndsDist[key]
         ? ndsDist[key]