fast-graph - npm Package Compare versions

Comparing version 1.2.0 to 1.3.0

package.json

 {
   "name": "fast-graph",
-  "version": "1.2.0",
+  "version": "1.3.0",
   "description": "A fast implementation of graph data structure",
@@ -5,0 +5,0 @@ "main": "lib/index.js",

README.md

@@ -123,2 +123,5 @@ # fast-graph
 });
+
+// Use Dijkstra's algorithm to discover shortest path from a node to all other nodes.
+const dijkstraResult: NodeDistance = graph.dijkstra(nodeA);
 ```
@@ -128,27 +131,15 @@
 
-## Algorithm guidelines
-
 ### Depth-First Search (DFS):
 
 1. **Traversal:**
-
    - DFS is commonly used for traversing or searching through a graph or tree data structure.
    - It explores as far as possible along each branch before backtracking.
-
 2. **Connected Components:**
-
    - DFS is used to identify connected components in an undirected graph.
-
 3. **Cycle Detection:**
-
    - DFS can be employed to detect cycles in a graph. If during the traversal, you encounter an already visited node, it indicates the presence of a cycle.
-
 4. **Pathfinding:**
-
    - DFS can help find paths between two nodes in a graph.
-
 5. **Maze Solving:**
-
    - DFS is useful for solving mazes and exploring possible paths.
-
 6. **Backtracking:**
@@ -160,38 +151,33 @@ - It's a fundamental algorithm for backtracking problems.
 1. **Shortest Path:**
-
    - BFS is commonly used to find the shortest path between two nodes in an unweighted graph.
-
 2. **Connected Components:**
-
    - Similar to DFS, BFS can identify connected components in an undirected graph.
-
 3. **Level Order Traversal:**
-
    - BFS is effective for performing level-order traversal of a tree or graph.
-
 4. **Maze Solving:**
-
    - BFS can be used for maze-solving algorithms.
-
 5. **Network Routing:**
    - BFS is applied in network routing protocols to discover the shortest path.
 
+### Dijkstra's Algorithm:
+
+1. **Shortest Paths:**
+   - Dijkstra's algorithm finds the shortest paths from a single source node to all other nodes in a graph with non-negative edge weights.
+2. **Non-Negative Weights:**
+   - It is particularly suited for graphs with non-negative weights, providing accurate shortest paths.
+3. **Applications:**
+   - Widely used in network routing, transportation systems, and any scenario where finding the shortest path is crucial.
+4. **Priority Queue:**
+   - Dijkstra's algorithm utilizes a priority queue to efficiently select the next node with the smallest tentative distance.
+
 ### Kahn's Topological Sort:
 
 1. **Directed Acyclic Graph (DAG):**
-
    - Kahn's algorithm is used for topological sorting of nodes in a Directed Acyclic Graph (DAG).
-
 2. **Dependency Resolution:**
-
    - In project management and build systems, Kahn's algorithm helps resolve dependencies between tasks or components.
-
 3. **Course Scheduling:**
-
    - In academic settings, Kahn's algorithm can be used for scheduling courses, ensuring prerequisites are met.
-
 4. **Task Execution Order:**
-
    - Kahn's algorithm is useful for determining the order of task execution when tasks have dependencies.
-
 5. **Compiler Dependency Analysis:**
@@ -203,13 +189,12 @@ - In compilers, Kahn's algorithm aids in analyzing and resolving dependencies between modules.
 - **Use DFS for...**
-
   - Exploring all possible paths in a graph.
   - Cycle detection.
   - Backtracking problems.
-
 - **Use BFS for...**
-
   - Finding the shortest path in an unweighted graph.
   - Level order traversal.
   - Maze solving.
-
+- **Use Dijkstra's Algorithm for...**
+  - Finding the shortest paths in graphs with non-negative weights.
+  - Applications requiring accurate shortest paths.
 - **Use Kahn's Algorithm for...**
@@ -216,0 +201,0 @@ - Topological sorting in Directed Acyclic Graphs.

No alert changes

Improved metrics

Total package byte prevSize

11030

increased by8.51%

Worsened metrics

Number of lines in readme file

214

decreased by-6.55%

No dependency changes