Is Evaluate Valid Expressions easy or hard?

Evaluate Valid Expressions is considered a hard problem because it combines string parsing, operator precedence handling, recursion, and stack-based evaluation. Correctly managing nested parentheses and intermediate calculations requires careful implementation and edge-case handling.

Evaluate Valid Expressions Python/Java solution

Python, Java, C++, Go, and TypeScript implementations typically use recursion combined with stack-based operator handling. The algorithm parses digits to build numbers, tracks the previous operator, and evaluates parentheses using recursive calls. Each implementation maintains O(n) time complexity.

How to solve Evaluate Valid Expressions in O(n)?

Scan the string once while maintaining the current number, operator, and a stack of partial results. When encountering parentheses, recursively evaluate the substring inside them. Apply multiplication and division immediately while pushing addition and subtraction values to the stack. This ensures each character is processed once, achieving O(n) time.

What is the best approach for Evaluate Valid Expressions?

The recursive divide-and-conquer approach is usually the best solution. It evaluates nested expressions by recursively processing parentheses while maintaining operator precedence with a stack or running accumulator. Each character is processed once, giving O(n) time complexity and O(n) space due to recursion and intermediate storage.

Is Evaluate Valid Expressions asked at Google/Amazon/Meta?

Expression parsing problems frequently appear in interviews at large tech companies including Google, Amazon, and Meta. Variations such as Basic Calculator, Evaluate Reverse Polish Notation, and expression tree evaluation test similar skills involving stacks, recursion, and string parsing.

What data structure is used in Evaluate Valid Expressions?

The most common data structure is a stack, which stores intermediate values while processing operators and maintaining precedence. Recursive solutions also use the call stack to evaluate nested parentheses. Some implementations use hash tables for memoization when caching repeated subexpressions.

What is the time complexity of Evaluate Valid Expressions?

The optimal solution runs in O(n) time where n is the length of the expression string. Each character is parsed once while numbers and operators are processed using constant-time stack or recursion operations. Space complexity is O(n) because of recursion depth and temporary storage for intermediate values.

3749. Evaluate Valid Expressions - Practice Online

You are given a string expression that represents a nested mathematical expression in a simplified form.

A valid expression is either an integer literal or follows the format op(a,b), where:

op is one of "add", "sub", "mul", or "div".
a and b are each valid expressions.

The operations are defined as follows:

add(a,b) = a + b
sub(a,b) = a - b
mul(a,b) = a * b
div(a,b) = a / b

Return an integer representing the result after fully evaluating the expression.

Example 1:

Input: expression = "add(2,3)"

Output: 5

Explanation:

The operation add(2,3) means 2 + 3 = 5.

Example 2:

Input: expression = "-42"

Output: -42

Explanation:

The expression is a single integer literal, so the result is -42.

Example 3:

Input: expression = "div(mul(4,sub(9,5)),add(1,1))"

Output: 8

Explanation:

First, evaluate the inner expression: sub(9,5) = 9 - 5 = 4
Next, multiply the results: mul(4,4) = 4 * 4 = 16
Then, compute the addition on the right: add(1,1) = 1 + 1 = 2
Finally, divide the two main results: div(16,2) = 16 / 2 = 8

Therefore, the entire expression evaluates to 8.

Constraints:

1 <= expression.length <= 10⁵
expression is valid and consists of digits, commas, parentheses, the minus sign '-', and the lowercase strings "add", "sub", "mul", "div".
All intermediate results fit within the range of a long integer.
All divisions result in integer values.