Stack Interview Questions Grouped by Technique

You are sitting in a technical interview, and the interviewer hands you an array problem. Your first instinct is a nested loop—an $O(N^2)$ brute force. But you know that will not get you the job. To crack top-tier product companies, you need to master the stack using our curated list of Stack Interview Questions Grouped by Technique. This guide provides an organized roadmap of problems categorized by exact solving patterns, helping you build core fundamentals similar to those taught in our Data Structures and Algorithms using Java course. If you prefer working in systems programming languages, you can also explore our Data Structures and Algorithms using C & C++ training or study Python implementations through our Data Structures and Algorithms using Python curriculum.

Why Group Stack Questions by Technique?

Grouping stack interview questions by technique is the fastest way to build pattern recognition. Instead of solving random problems, learning the underlying blueprints—like Monotonic Stacks, Parentheses Matching, or Design Patterns—helps you solve unseen problems on the fly. When you see a new problem, you will not scramble; you will immediately classify it and apply the correct template. Once you master stack patterns, transition to FIFO structures using our Queue Interview Roadmap: Grouped by Patterns and LeetCode Links or explore the Arrays Interview Roadmap: 138 Questions Mapped by Technique for complete coverage.

Technique 1: Monotonic Stack (The Powerhouse)

• Next Greater Element I - Find the next larger element for subset arrays.
• Next Greater Element II - Handle circular arrays using a virtual double pass.
• Daily Temperatures - Calculate the number of days until a warmer temperature.
• Online Stock Span - Track consecutive days of lower or equal prices.
• Largest Rectangle in Histogram - Find the maximum rectangular area in a bar chart.
• Maximal Rectangle - Maximize 1s in a 2D binary matrix using histogram logic.
• Trapping Rain Water - Compute water trapped between elevation maps.
• Sum of Subarray Minimums - Find the sum of minimum values of all subarrays.
• Sum of Subarray Ranges - Calculate the difference between max and min subarray elements.
• 132 Pattern - Search for a specific subsequence pattern using a decreasing stack.
• Remove K Digits - Minimize a number by removing K digits sequentially.
• Create Maximum Number - Build the largest possible number from two arrays.
• Remove Duplicate Letters - Find the lexicographically smallest unique character string.
• Smallest Subsequence of Distinct Characters - Maintain relative order while removing duplicates.
• Steps to Make Array Non-decreasing - Count steps to clean up an array using a step-tracking stack.

import java.util.ArrayDeque;
import java.util.Deque;
import java.util.Arrays;

public class MonotonicStackExample {
    public static int[] nextGreaterElement(int[] nums) {
        int[] result = new int[nums.length];
        Arrays.fill(result, -1);
        Deque<Integer> stack = new ArrayDeque<>();
        
        for (int i = 0; i < nums.length; i++) {
            while (!stack.isEmpty() && nums[stack.peek()] < nums[i]) {
                int index = stack.pop();
                result[index] = nums[i];
            }
            stack.push(i);
        }
        return result;
    }

    public static void main(String[] args) {
        int[] input = {2, 1, 2, 4, 3};
        System.out.println(Arrays.toString(nextGreaterElement(input)));
    }
}

Technique 2: Parentheses and Nesting

These problems involve matching pairs, validating nested structures, or resolving expressions. Stacks are perfect here because the last opened bracket must be the first one closed.

• Valid Parentheses - The classic matching bracket problem.
• Generate Parentheses - Generate all combinations of well-formed brackets.
• Longest Valid Parentheses - Find the length of the longest valid substring.
• Minimum Add to Make Parentheses Valid - Count required insertions for validity.
• Minimum Remove to Make Valid Parentheses - Clean up unbalanced strings by track indices.
• Score of Parentheses - Compute scores based on nested depth.
• Check if Word Is Valid After Substitutions - Validate strings formed by repeating patterns.
• Different Ways to Add Parentheses - Compute all possible expression evaluations.
• Maximum Nesting Depth of the Parentheses - Find the deepest level of nested brackets.
• Minimum Number of Swaps to Make the String Balanced - Balance bracket strings with minimal swaps.

Technique 3: Expression Parsing and Calculators

Computers do not read expressions like humans. Stacks help convert infix expressions to postfix/prefix and evaluate arithmetic operations by maintaining operator precedence.

• Basic Calculator - Handle addition, subtraction, and brackets.
• Basic Calculator II - Add multiplication and division precedence.
• Basic Calculator III - Support all operators plus nested parentheses.
• Evaluate Reverse Polish Notation - Evaluate postfix mathematical expressions.
• Decode String - Unpack nested encoded strings like 3[a]2[bc].
• Mini Parser - Parse a nested list of integers from a string.
• Ternary Expression Parser - Evaluate right-to-left ternary logic.
• Parse Lisp Expression - Handle variable scoping and complex Lisp evaluations.
• Asteroid Collision - Simulate opposite-moving objects colliding in a space.
• Robot Collisions - Calculate surviving robots using health and direction.

Technique 4: System and Data Structure Design

These questions ask you to build custom data structures or mimic stack behavior using other storage formats. They test object-oriented design alongside core algorithmic skills.

• Min Stack - Retrieve the minimum element in O(1) time.
• Max Stack - Retrieve the maximum element in O(1) time.
• Implement Queue using Stacks - Mimic FIFO behavior using two LIFO structures.
• Implement Stack using Queues - Mimic LIFO behavior using FIFO structures.
• Peeking Iterator - Design an iterator that can look ahead.
• Design a Stack With Increment Operation - Support bulk increments efficiently.
• Dinner Plate Stacks - Manage a row of stacks with capacity limits.
• Design Browser History - Build back and forward navigation features.
• Flatten Nested List Iterator - Flatten nested lists lazily using a stack.
• All O`one Data Structure - Maintain min/max frequencies in constant time.

Technique 5: Tree and Graph Traversal (Iterative)

While recursion is clean, interviewers love to ask for iterative traversals to test your understanding of the call stack. Use an explicit stack to mimic recursion.

• Binary Tree Inorder Traversal - Left-Root-Right traversal using a stack.
• Binary Tree Preorder Traversal - Root-Left-Right traversal.
• Binary Tree Postorder Traversal - Left-Right-Root traversal (often requires two stacks).
• Binary Search Tree Iterator - Implement O(1) next() average-time iterator.
• Verify Preorder Sequence in Binary Search Tree - Validate BST preorder arrays.
• Construct Binary Tree from Preorder and Postorder Traversal - Rebuild tree structure.
• Find Duplicate Subtrees - Identify repeating structures using serialization.
• Clone Graph - Deep copy an undirected graph using iterative DFS.
• Course Schedule II - Find topological order using DFS stack.
• Number of Islands - Traverse connected components iteratively.

Technique 6: Array Manipulation and Simulation

These problems require simulating a process or tracking history. The LIFO nature of stacks makes it easy to revert states or process elements in reverse order of discovery.

• Simplify Path - Resolve Unix-style absolute paths.
• Backspace String Compare - Process strings containing backspace characters.
• Build an Array With Stack Operations - Simulate target array construction.
• Baseball Game - Keep score with dynamic record operations.
• Crawler Log Folder - Track folder depth transitions.
• Validate Stack Sequences - Check if push and pop sequences are compatible.
• Exclusive Time of Functions - Calculate single-thread execution times.
• Car Fleet - Determine how many groups of cars reach a destination.
• Car Fleet II - Solve for collision times in a multi-car system.
• Flatten a Multilevel Doubly Linked List - Flatten nested lists using child pointers.

Technique 7: Advanced and Hard Stack Problems

These problems combine multiple techniques, requiring deep analytical skill and clean state management. They are common in senior-level engineering loops.

• Remove Duplicate Letters - Lexicographical processing with frequency tracking.
• Maximum Frequency Stack - Pop the most frequent element first.
• Tag Validator - Parse and validate complex custom HTML/XML tags.
• Number of Visible Peaks - Find visible peaks under line-of-sight constraints.
• Subarray With Elements Greater Than Varying Threshold - Advanced range search.
• Find the Most Competitive Subsequence - Build optimal subsequences using size-bounded stacks.
• Minimum Cost Tree From Leaf Values - Optimize tree construction values.
• Odd Even Jump - Jump game variant utilizing monotonic stack lookups.
• Symmetric Tree - Verify mirror symmetry iteratively.
• Check If a Parentheses String Can Be Valid - Handle wildcards in bracket strings.

To truly master stack interview questions, do not try to memorize all 70. Instead, pick 2 or 3 questions from each of these seven techniques. Focus on why the stack was the correct choice, how the state changes on each push or pop, and how to optimize your space complexity. Once you feel comfortable with stacks, transition to linear data structures with our String Interview Roadmap: 66 Questions Grouped by Technique to keep your preparation structured.