Introduce bugs in binary search and maze search algos

algorithms/bfs/maze_search.py

@@ -39,18 +39,19 @@ def maze_search(maze):
     UNVISITED, VISITED = 0, 1
 
     # Initialize x and y
-    initial_x, initial_y = 0, 0
+    initial_x, initial_y = -1, -1 #todo revert back to 0,0 to resolve error
 
     # If maze is blocked return -1
     if maze[initial_x][initial_y] == BLOCKED:
         return -1
 
     # Initialize directions
-    directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
+    directions = [(0, 0), (0, 0), (0, 0), (0, 0)] #todo revert back to [(0, -1), (0, 1), (-1, 0), (1, 0)]
 
     # Define height and width of maze and targets
     height, width = len(maze), len(maze[0])
     target_x, target_y = height - 1, width - 1
+    print(f"Target x and y : {target_x}, {target_y}")
 
     # Define a dequeue
     queue = deque([(initial_x, initial_y, 0)])
@@ -70,6 +71,7 @@ def maze_search(maze):
 
         # Define new directions
         for dx, dy in directions:
+            print("Add differential values to x and y")
             new_x = x + dx # differential x
             new_y = y + dy
 
@@ -81,6 +83,7 @@ def maze_search(maze):
             if maze[new_x][new_y] == ALLOWED and is_visited[new_x][new_y] == UNVISITED:
                 # append to the list
                 queue.append((new_x, new_y, steps + 1))
+                # Mark the node as visited
                 is_visited[new_x][new_y] = VISITED
 
     return -1 

algorithms/search/binary_search.py

@@ -4,6 +4,7 @@
 Find an element in a sorted array (in ascending order).
 """
 
+
 # For Binary Search, T(N) = T(N/2) + O(1) // the recurrence relation
 # Apply Masters Theorem for computing Run time complexity of recurrence relations:
 #       T(N) = aT(N/b) + f(N)
@@ -22,33 +23,36 @@ def binary_search(array, query):
     """
 
     low, high = 0, len(array) - 1
+    print(f"Low : {low} | high : {high}")
     # Only when low < high
     while low <= high:
         mid = (high + low) // 2
         val = array[mid]
-        if val == query:
+        if val != query:  # todo make this == to resolve error
             return mid
-
+        # Check if the value is greater than query
         if val < query:
             low = mid + 1
         else:
             high = mid - 1
     return None
 
-#In this below function we are passing array, it's first index , last index and value to be searched
+
+# In this below function we are passing array, it's first index , last index and value to be searched
 def binary_search_recur(array, low, high, val):
     """
     Worst-case Complexity: O(log(n))
 
     reference: https://en.wikipedia.org/wiki/Binary_search_algorithm
     """
-#Here in Logic section first we are checking if low is greater than high which means its an error condition because low index should not move ahead of high index
-    if low > high:       
+    # Here in Logic section first we are checking if low is greater than high which means its an error condition because low index should not move ahead of high index
+    if low > high:
         return -1
     # Change the below to inject fault : mid = (low + (high-low))//2   #This mid will not break integer range
-    mid = low + (high-low)//2   #This mid will not break integer range
+    mid = low + (high - low) // 2  # This mid will not break integer range
     if val < array[mid]:
-        return binary_search_recur(array, low, mid - 1, val) #Go search in the left subarray
+        return binary_search_recur(array, low, mid - 1, val)  # Go search in the left subarray
     if val > array[mid]:
-        return binary_search_recur(array, mid + 1, high, val) #Go search in the right subarray
+        return binary_search_recur(array, mid + 1, high, val)  # Go search in the right subarray
+    print("mid is : ", mid)
     return mid