diff --git a/KislyuninED/docks/data/2-st-exercize/maze-plots.py b/KislyuninED/docks/data/2-st-exercize/maze-plots.py
new file mode 100644
index 0000000..22e7625
--- /dev/null
+++ b/KislyuninED/docks/data/2-st-exercize/maze-plots.py
@@ -0,0 +1,402 @@
+import sys
+import csv
+from collections import deque
+import heapq
+import time
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+class Cell:
+    def __init__(self, x, y):
+        self._x = x
+        self._y = y
+        self._is_wall = False
+        self._is_start = False
+        self._is_exit = False
+    
+    @property
+    def x(self):
+        return self._x
+    
+    @property
+    def y(self):
+        return self._y
+    
+    @property
+    def is_wall(self):
+        return self._is_wall
+    
+    @is_wall.setter
+    def is_wall(self, value):
+        self._is_wall = value
+    
+    @property
+    def is_start(self):
+        return self._is_start
+    
+    @is_start.setter
+    def is_start(self, value):
+        self._is_start = value
+    
+    @property
+    def is_exit(self):
+        return self._is_exit
+    
+    @is_exit.setter
+    def is_exit(self, value):
+        self._is_exit = value
+    
+    def is_passable(self):
+        return not self._is_wall
+
+
+class Maze:
+    def __init__(self, width, height):
+        self._width = width
+        self._height = height
+        self._cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
+        self._start = None
+        self._exit = None
+    
+    @property
+    def width(self):
+        return self._width
+    
+    @property
+    def height(self):
+        return self._height
+    
+    @property
+    def start(self):
+        return self._start
+    
+    @property
+    def exit(self):
+        return self._exit
+    
+    def get_cell(self, x, y):
+        if 0 <= x < self._width and 0 <= y < self._height:
+            return self._cells[y][x]
+        return None
+    
+    def set_cell(self, x, y, cell_type):
+        cell = self.get_cell(x, y)
+        if cell is None:
+            return
+        
+        if cell_type == 'wall':
+            cell.is_wall = True
+        elif cell_type == 'start':
+            if self._start:
+                self._start.is_start = False
+            cell.is_start = True
+            cell.is_wall = False
+            self._start = cell
+        elif cell_type == 'exit':
+            if self._exit:
+                self._exit.is_exit = False
+            cell.is_exit = True
+            cell.is_wall = False
+            self._exit = cell
+        elif cell_type == 'path':
+            cell.is_wall = False
+    
+    def get_neighbors(self, cell):
+        neighbors = []
+        directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
+        for dx, dy in directions:
+            nx, ny = cell.x + dx, cell.y + dy
+            neighbor = self.get_cell(nx, ny)
+            if neighbor and neighbor.is_passable():
+                neighbors.append(neighbor)
+        return neighbors
+
+
+class MazeBuilder:
+    def build_from_file(self, filename):
+        raise NotImplementedError
+
+
+class TextFileMazeBuilder(MazeBuilder):
+    def build_from_file(self, filename):
+        with open(filename, 'r') as f:
+            lines = [line.rstrip('\n') for line in f.readlines()]
+        height = len(lines)
+        width = max(len(line) for line in lines) if height > 0 else 0
+        start_en = 0
+        exit_en = 0
+        maze = Maze(width, height)
+
+        for y, line in enumerate(lines):
+            for x, ch in enumerate(line):
+                if ch == "#":
+                    maze.set_cell(x, y, "wall")
+                elif ch == "S":
+                    maze.set_cell(x, y, "start")
+                    start_en += 1
+                elif ch == "E":
+                    maze.set_cell(x, y, "exit")
+                    exit_en += 1
+                else:
+                    maze.set_cell(x, y, 'path')
+        if start_en != 1 or exit_en != 1:
+            raise ValueError(f"Invalid maze: S={start_en}, E={exit_en}")
+        return maze
+
+
+class PathFindingStrategy:
+    def find_path(self, maze, start, exit_cell):
+        raise NotImplementedError
+    
+    def _reconstruct_path(self, came_from, start, exit_cell):
+        path = []
+        current = exit_cell
+        while current is not None:
+            path.append(current)
+            current = came_from.get(current)
+        path.reverse()
+        return path
+    
+    def get_visited_count(self):
+        return getattr(self, '_visited_count', 0)
+
+
+class BFSStrategy(PathFindingStrategy):
+    def find_path(self, maze, start, exit_cell):
+        queue = deque()
+        queue.append(start)
+        came_from = {start: None}
+        visited = {start}
+        
+        while queue:
+            current = queue.popleft()
+            if current == exit_cell:
+                self._visited_count = len(visited)
+                return self._reconstruct_path(came_from, start, exit_cell)
+            for neighbor in maze.get_neighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    came_from[neighbor] = current
+                    queue.append(neighbor)
+        self._visited_count = len(visited)
+        return []
+
+
+class DFSStrategy(PathFindingStrategy):
+    def find_path(self, maze, start, exit_cell):
+        stack = [start]
+        came_from = {start: None}
+        visited = {start}
+        
+        while stack:
+            current = stack.pop()
+            if current == exit_cell:
+                self._visited_count = len(visited)
+                return self._reconstruct_path(came_from, start, exit_cell)
+            for neighbor in maze.get_neighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    came_from[neighbor] = current
+                    stack.append(neighbor)
+        self._visited_count = len(visited)
+        return []
+
+
+class AStarStrategy(PathFindingStrategy):
+    def _heuristic(self, cell, exit_cell):
+        return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
+    
+    def find_path(self, maze, start, exit_cell):
+        heap = []
+        counter = 0
+        start_f = self._heuristic(start, exit_cell)
+        heapq.heappush(heap, (start_f, counter, start))
+        counter += 1
+        
+        came_from = {}
+        g_score = {start: 0}
+        f_score = {start: start_f}
+        visited = set()
+        
+        while heap:
+            current_f, _, current = heapq.heappop(heap)
+            visited.add(current)
+            
+            if current == exit_cell:
+                self._visited_count = len(visited)
+                return self._reconstruct_path(came_from, start, exit_cell)
+            if current_f > f_score.get(current, float('inf')):
+                continue
+            for neighbor in maze.get_neighbors(current):
+                tentative_g = g_score[current] + 1
+                if tentative_g < g_score.get(neighbor, float('inf')):
+                    came_from[neighbor] = current
+                    g_score[neighbor] = tentative_g
+                    new_f = tentative_g + self._heuristic(neighbor, exit_cell)
+                    f_score[neighbor] = new_f
+                    heapq.heappush(heap, (new_f, counter, neighbor))
+                    counter += 1
+        self._visited_count = len(visited)
+        return []
+
+
+class MazeSolver:
+    def __init__(self, maze):
+        self._maze = maze
+        self._strategy = None
+    
+    def set_strategy(self, strategy):
+        self._strategy = strategy
+    
+    def solve(self):
+        if self._strategy is None:
+            return None
+        
+        start_time = time.perf_counter()
+        path = self._strategy.find_path(self._maze, self._maze.start, self._maze.exit)
+        end_time = time.perf_counter()
+        time_ms = (end_time - start_time) * 1000
+        
+        return {
+            'time_ms': time_ms,
+            'visited_cells': self._strategy.get_visited_count(),
+            'path_length': len(path)
+        }
+
+
+def run_experiment(maze_file, strategy, runs=5):
+    builder = TextFileMazeBuilder()
+    maze = builder.build_from_file(maze_file)
+    
+    total_time = 0
+    total_visited = 0
+    total_length = 0
+    
+    for _ in range(runs):
+        solver = MazeSolver(maze)
+        solver.set_strategy(strategy)
+        stats = solver.solve()
+        if stats:
+            total_time += stats['time_ms']
+            total_visited += stats['visited_cells']
+            total_length += stats['path_length']
+    
+    return {
+        'time_ms': total_time / runs,
+        'visited_cells': total_visited / runs,
+        'path_length': total_length / runs
+    }
+
+
+def generate_plots(results):
+    mazes = list(set([r['maze'] for r in results]))
+    strategies = ['BFS', 'DFS', 'AStar']
+    
+    fig, axes = plt.subplots(1, 3, figsize=(15, 5))
+    
+    x = np.arange(len(mazes))
+    width = 0.25
+    
+    for i, strat in enumerate(strategies):
+        times = []
+        for maze in mazes:
+            val = next((r['time_ms'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
+            times.append(val)
+        axes[0].bar(x + i*width, times, width, label=strat)
+    
+    axes[0].set_xlabel('Maze')
+    axes[0].set_ylabel('Time (ms)')
+    axes[0].set_title('Execution Time Comparison')
+    axes[0].set_xticks(x + width)
+    axes[0].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[0].legend()
+    axes[0].grid(True, alpha=0.3)
+    
+    for i, strat in enumerate(strategies):
+        visited = []
+        for maze in mazes:
+            val = next((r['visited_cells'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
+            visited.append(val)
+        axes[1].bar(x + i*width, visited, width, label=strat)
+    
+    axes[1].set_xlabel('Maze')
+    axes[1].set_ylabel('Visited Cells')
+    axes[1].set_title('Visited Cells Comparison')
+    axes[1].set_xticks(x + width)
+    axes[1].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[1].legend()
+    axes[1].grid(True, alpha=0.3)
+    
+    for i, strat in enumerate(strategies):
+        lengths = []
+        for maze in mazes:
+            val = next((r['path_length'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
+            lengths.append(val)
+        axes[2].bar(x + i*width, lengths, width, label=strat)
+    
+    axes[2].set_xlabel('Maze')
+    axes[2].set_ylabel('Path Length')
+    axes[2].set_title('Path Length Comparison')
+    axes[2].set_xticks(x + width)
+    axes[2].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[2].legend()
+    axes[2].grid(True, alpha=0.3)
+    
+    plt.tight_layout()
+    plt.savefig('performance_comparison_2-nd-exercise.png', dpi=150, bbox_inches='tight')
+    plt.show()
+
+
+if __name__ == "__main__":
+    mazes = [
+        ("maze1.txt", "Small 10x6"),
+        ("maze10x10.txt", "Medium 10x10"),
+        ("maze20x20.txt", "Large 20x20"),
+        ("maze_empty.txt", "Empty 15x15"),
+        ("maze_no_exit.txt", "No exit 10x10")
+    ]
+    
+    strategies = [
+        ("BFS", BFSStrategy()),
+        ("DFS", DFSStrategy()),
+        ("AStar", AStarStrategy())
+    ]
+    
+    results = []
+    
+    for maze_file, maze_name in mazes:
+        print(f"Testing {maze_name}...")
+        for strat_name, strat in strategies:
+            try:
+                stats = run_experiment(maze_file, strat, runs=3)
+                results.append({
+                    'maze': maze_name,
+                    'strategy': strat_name,
+                    'time_ms': stats['time_ms'],
+                    'visited_cells': stats['visited_cells'],
+                    'path_length': stats['path_length']
+                })
+                print(f"  {strat_name}: time={stats['time_ms']:.3f}ms, visited={stats['visited_cells']:.0f}, length={stats['path_length']:.0f}")
+            except Exception as e:
+                print(f"  {strat_name}: ERROR - {e}")
+                results.append({
+                    'maze': maze_name,
+                    'strategy': strat_name,
+                    'time_ms': -1,
+                    'visited_cells': -1,
+                    'path_length': -1
+                })
+    
+    valid_results = [r for r in results if r['time_ms'] >= 0]
+    
+    with open('experiment_results_2-nd-exercise.csv', 'w', newline='', encoding='utf-8') as f:
+        writer = csv.DictWriter(f, fieldnames=['maze', 'strategy', 'time_ms', 'visited_cells', 'path_length'])
+        writer.writeheader()
+        writer.writerows(valid_results)
+    
+    if valid_results:
+        generate_plots(valid_results)
+    
+    print("\nResults saved to experiment_results_2-nd-exercise.csv")
+    print("Plot saved to performance_comparison_2-nd-exercise.png")
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