How do you solve Basic Calculator IV on LeetCode?

Basic Calculator IV (LeetCode #770) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Understanding polynomial representation simplifies complex expressions.

What is the brute force solution for Basic Calculator IV?

The brute force approach for Basic Calculator IV is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves parsing the expression and evaluating it directly by handling each operation step by step. This method is straightforward but inefficient, as it may require multiple passes through the expression. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Basic Calculator IV?

Basic Calculator IV uses the following concepts: Hash Table, Math, String, Stack, Recursion. The recommended patterns to study are: Hash Map, Polynomial Representation.

What are the interview tips for Basic Calculator IV?

Explain your thought process clearly while coding. Break down the problem into smaller parts before implementing. Practice parsing expressions and managing operator precedence.

What are common mistakes when solving Basic Calculator IV?

Not handling parentheses correctly during parsing. Failing to combine like terms properly.

#770

Basic Calculator IV

Hard

Hash TableMathStringStackRecursionHash MapPolynomial Representation

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal approach involves creating a Polynomial class to represent expressions, allowing for efficient addition, subtraction, and multiplication of terms. This structure simplifies the evaluation process and allows us to handle complex expressions more effectively.

⚙️

Algorithm

4 steps

1Step 1: Create a Polynomial class with methods for addition, subtraction, multiplication, and evaluation.
2Step 2: Parse the expression into Polynomial objects.
3Step 3: Use the Polynomial methods to combine and evaluate the parsed expressions based on the provided eval map.
4Step 4: Format the final result into the required output format.

solution.py24 lines

1class Polynomial:
2    def __init__(self):
3        self.terms = {}
4    def add(self, other):
5        # Implementation for adding two polynomials
6        pass
7    def sub(self, other):
8        # Implementation for subtracting two polynomials
9        pass
10    def mul(self, other):
11        # Implementation for multiplying two polynomials
12        pass
13    def evaluate(self, eval_map):
14        # Implementation for evaluating the polynomial
15        pass
16    def to_list(self):
17        # Implementation for converting to list
18        pass
19
20class Solution:
21    def basicCalculatorIV(self, expression, evalvars, evalints):
22        eval_map = dict(zip(evalvars, evalints))
23        # Parse and evaluate using Polynomial class
24        return []

ℹ

Complexity note: The optimal solution runs in linear time because each term is processed once, and the space complexity is linear due to storing polynomial terms.

1Understanding polynomial representation simplifies complex expressions.
2Using a structured approach allows for better management of terms and operations.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.