# Dijkstras Two Stack Algorithm

Dijkstra's Two-Stack Algorithm is a method used to evaluate arithmetic expressions in postfix notation (also known as Reverse Polish Notation or RPN) without using parentheses. The algorithm uses two stacks, one for operands and one for operators, to perform the evaluation.

Let's start by explaining the algorithm in detail and then provide an example of solving an arithmetic expression using this algorithm.

Dijkstra's Two-Stack Algorithm:

- Create two empty stacks: one for operands and one for operators.
- Iterate through the expression from left to right.
- If the current token is a number, push it onto the operand stack.
- If the current token is an operator, push it onto the operator stack.
- If the current token is a closing parenthesis (which is not used in postfix notation), pop an operator from the operator stack, pop the required number of operands from the operand stack based on the arity of the operator, perform the operation, and push the result back onto the operand stack.
- Continue the process until all tokens in the expression are processed.
- At the end, the operand stack will contain the final result of the expression.

Now, let's solve a question "Evaluate Reverse Polish Notation" using Dijkstra's Two-Stack Algorithm.

Problem: Given an arithmetic expression in postfix notation, evaluate it and return the result.

Here's the solution code in Python with proper comments explaining each step:

```
def evalRPN(tokens):
operand_stack = [] # Stack to store operands
for token in tokens:
if token.isdigit() or (token[0] == '-' and token[1:].isdigit()):
# If the token is a number, push it onto the operand stack
operand_stack.append(int(token))
else:
# If the token is an operator, pop the required number of operands from the stack, perform the operation, and push the result back onto the stack
operand2 = operand_stack.pop()
operand1 = operand_stack.pop()
if token == '+':
result = operand1 + operand2
elif token == '-':
result = operand1 - operand2
elif token == '*':
result = operand1 * operand2
else:
# In Python 3, division of two integers returns a float
result = int(operand1 / operand2)
operand_stack.append(result)
# The operand stack will contain the final result of the expression
return operand_stack[0]
```

In this code, we iterate through each token in the expression. If the token is a number, we convert it to an integer and push it onto the operand stack. If the token is an operator, we pop the required number of operands from the operand stack based on the arity of the operator. We then perform the operation and push the result back onto the operand stack.

At the end of the iteration, the operand stack will contain the final result of the expression, which we return.

### Time and Space Complexity

The time complexity of the `evalRPN`

function is O(n), where n is the number of tokens in the input expression. We iterate through each token once and perform constant-time operations for each token.

The space complexity of the implementation is O(n) in the worst case. This occurs when all the tokens in the expression are numbers, and they are pushed onto the operand stack.

I'll explain the concept of Dijkstra's Two-Stack Algorithm using Python and provide you with complete code.

Dijkstra's Two-Stack Algorithm is a method used to evaluate arithmetic expressions in postfix notation without using parentheses. It utilizes two stacks: one for operands and one for operators. The algorithm scans the expression from left to right and performs the necessary operations based on the encountered tokens.

Here's a step-by-step explanation of the algorithm:

- Create two empty stacks: one for operands and one for operators.
- Iterate through the expression from left to right.
- If the current token is a number, push it onto the operand stack.
- If the current token is an operator, pop the required number of operands from the operand stack based on the arity of the operator, perform the operation, and push the result back onto the operand stack.
- Continue the process until all tokens in the expression are processed.
- At the end, the operand stack will contain the final result of the expression.

Now, let's write the complete code for implementing Dijkstra's Two-Stack Algorithm in Python:

```
def evaluate_expression(expression):
operand_stack = [] # Stack to store operands
for token in expression:
if token.isdigit():
# If the token is a number, push it onto the operand stack
operand_stack.append(int(token))
else:
# If the token is an operator, pop the required number of operands, perform the operation, and push the result back onto the stack
operand2 = operand_stack.pop()
operand1 = operand_stack.pop()
if token == '+':
result = operand1 + operand2
elif token == '-':
result = operand1 - operand2
elif token == '*':
result = operand1 * operand2
else:
# In Python 3, division of two integers returns a float
result = int(operand1 / operand2)
operand_stack.append(result)
# The operand stack will contain the final result of the expression
return operand_stack[0]
```

In this code, the `evaluate_expression`

function takes an expression in postfix notation as input and returns the evaluated result. The function iterates through each token in the expression. If the token is a number, it is converted to an integer and pushed onto the operand stack. If the token is an operator, the required number of operands are popped from the stack, the operation is performed, and the result is pushed back onto the stack.

Finally, the function returns the top element of the operand stack, which represents the evaluated result of the expression.

I hope this explanation and code help you understand Dijkstra's Two-Stack Algorithm in Python!

In this code, we define the `evaluate_expression`

function as explained before. We also include an example usage where we define an expression in postfix notation `['4', '2', '+', '3', '*']`

. We pass this expression to the `evaluate_expression`

function, and the result is stored in the `result`

variable. Finally, we print the result.

To demonstrate the usage of Dijkstra's Two-Stack Algorithm and analyze its time and space complexity, let's solve a question : "Evaluate Reverse Polish Notation"

Problem Statement: Given an arithmetic expression in Reverse Polish Notation (RPN), evaluate it and return the result.

Example: Input: tokens = ["2", "1", "+", "3", "*"] Output: 9 Explanation: ((2 + 1) * 3) = 9

Now, let's write the code to solve this problem using Dijkstra's Two-Stack Algorithm:

```
def evaluate_expression(expression):
operand_stack = [] # Stack to store operands
for token in expression:
if token.isdigit():
# If the token is a number, push it onto the operand stack
operand_stack.append(int(token))
else:
# If the token is an operator, pop the required number of operands, perform the operation, and push the result back onto the stack
operand2 = operand_stack.pop()
operand1 = operand_stack.pop()
if token == '+':
result = operand1 + operand2
elif token == '-':
result = operand1 - operand2
elif token == '*':
result = operand1 * operand2
else:
# In Python 3, division of two integers returns a float
result = int(operand1 / operand2)
operand_stack.append(result)
# The operand stack will contain the final result of the expression
return operand_stack[0]
# Example usage
expression = ['4', '2', '+', '3', '*']
result = evaluate_expression(expression)
print(f"Result: {result}")
```

The `evalRPN`

function takes a list of tokens as input and evaluates the RPN expression using Dijkstra's Two-Stack Algorithm. The function iterates through each token in the input list and performs the required operations accordingly. Finally, it returns the result obtained from the operand stack.

Time Complexity: The time complexity of this algorithm is O(n), where n is the number of tokens in the input expression. This is because we iterate through each token once, and each operation takes constant time.

Space Complexity: The space complexity of this algorithm is O(n), where n is the number of tokens in the input expression. This is because we use a stack to store the operands, and the size of the stack can be at most n/2 in the worst case (when all tokens are operands).

Overall, Dijkstra's Two-Stack Algorithm provides an efficient approach to evaluate arithmetic expressions in RPN, with a linear time complexity.