diff --git a/challenges/maze-solver/description.md b/challenges/maze-solver/description.md
index 735babd..8ca50fc 100644
--- a/challenges/maze-solver/description.md
+++ b/challenges/maze-solver/description.md
@@ -1,19 +1,17 @@
-# Maze Solver
-
-In this challenge, you will implement a maze solver in Rust. A maze can be represented as a grid where each cell is either an open path or a wall. The goal is to navigate from a starting point to an ending point using the shortest path possible. This problem will test your understanding of control flow in Rust, including loops, conditionals, and possibly recursion.
+In this challenge, you will implement a **maze solver in Rust**. A maze can be represented as a **grid where each cell is either an open path or a wall**. The goal is to navigate from a starting point to an ending point using the shortest path possible. This problem will test your understanding of control flow in Rust, including loops, conditionals, and possibly recursion.
 
 ## Your Task
 
-Your task is to write a function `solve_maze` that takes a 2D vector of characters representing the maze and two tuples representing the start and end points. The maze will be given as a grid of characters where 'S' represents the start, 'E' represents the end, '.' represents an open path, and '#' represents a wall.
+Your task is to write a function `solve_maze` that takes a **2D vector of characters representing the maze and two tuples representing the start and end points.** The maze will be given as a grid of characters where `'S'` represents the start, `'E'` represents the end, `'.'` represents an open path, and `'#'` represents a wall.
 
-The function should return a vector of tuples representing the path from start to end if a path exists, or an empty vector if no path exists.
+**The function should return a vector of tuples** representing the path from start to end if a path exists, or an empty vector if no path exists.
 
-## Requirements
+## Constraints
 
-- The maze will always contain exactly one 'S' and one 'E'.
-- You can only move up, down, left, or right.
-- Implement the function using appropriate control flow constructs (loops, conditionals, and/or recursion).
-- Ensure your solution handles edge cases, such as no available path or mazes with various sizes.
+- The maze will always contain exactly one `'S'` and one `'E'`.
+- You can only move **up, down, left, or right**.
+- Implement the function using appropriate control flow constructs **(loops, conditionals, and/or recursion)**.
+- Ensure your solution **handles edge cases**, such as no available path or mazes with various sizes.
 
 ## Example
 
@@ -29,16 +27,44 @@ let start = (0, 0);
 let end = (4, 3);
 
 let path = solve_maze(maze, start, end);
-assert_eq!(path, vec![(0, 0), (1, 0), (2, 1), (2, 2), (3, 2), (4, 2), (4, 3)]);
+assert_eq!(
+    path,
+    vec![
+        (0, 0), // starting point
+        (0, 1), // right
+        (1, 1), // down
+        (2, 1), // down
+        (2, 2), // right
+        (2, 3), // right
+        (3, 3), // down
+        (4, 3) // down
+    ]
+);
 ```
 
+In the example above, we start from `'S'` at `(0, 0)`, the first move would be going to the right `(0, 1)`, then down `(1, 1)`, and so on until we reach the end at `(4, 3)`.
+
 > Did You Know?
 >
 > Maze solving algorithms are not just for games. They are used in robotics for **pathfinding**, in computer networks for routing, and in various optimization problems. Algorithms such as Depth-First Search (DFS), Breadth-First Search (BFS), and A\* are commonly used to solve these problems efficiently.
 
 ## Hints
 
-- Start by implementing a simple depth-first search (DFS) or breadth-first search (BFS) to explore the maze.
-- Consider using a queue for BFS or a stack for DFS to manage the cells to be explored.
-- Keep track of visited cells to avoid infinite loops.
-- Think about how you can reconstruct the path once you find the end.
+1. **Collections**:
+
+   - `VecDeque`: A double-ended queue from the `std::collections` module, which is useful for implementing a queue for BFS. Methods like `push_back` and `pop_front` will be helpful.
+
+2. **Indexing**:
+
+   - Use `usize` for indices and be cautious with arithmetic operations to avoid overflow. The `wrapping_add` method can help with safe arithmetic.
+
+3. **2D Vector Initialization**:
+
+   - Initialize 2D vectors for `visited` and `path` tracking. Use nested `vec!` macros for creating the initial structure.
+
+4. **Backtracking Path**:
+
+   - Once the end point is reached, backtrack using the `path` vector to reconstruct the path from end to start. Collect these coordinates in a vector and reverse it to get the path from start to end.
+
+5. **Boundary Checks**:
+   - Ensure the new coordinates are within the maze boundaries and check if the cell is a wall (`'#'`) or already visited.