How to Crack Ericsson Coding Interviews in 2026

Ericsson’s coding interviews are a critical gateway for software and network engineering roles. The process typically involves one or two technical rounds focusing on problem-solving, data structures, and algorithms, often conducted via a coding platform. While the questions test fundamental competency, their specific distribution and topical focus require a targeted approach.

By the Numbers — Difficulty Breakdown and What It Means

The data reveals a distinct pattern: a heavy skew towards Easy questions (67%) with a significant spike for Hard questions (33%). There are no Medium-difficulty problems in this sample.

This distribution is strategic. The Easy questions act as a filter, assessing basic coding fluency, attention to detail, and the ability to deliver clean, working code under interview conditions. Failing here is often a non-starter. The solitary Hard question serves as a differentiator, designed to separate competent candidates from exceptional ones. It tests advanced problem-solving, familiarity with complex data structures (like the Trie), and the stamina to navigate a multi-step problem. Your preparation must account for this bimodal spread: flawless execution on fundamentals and dedicated practice for high-complexity challenges.

Top Topics to Focus On

Your study should prioritize these areas, which cover the core of Ericsson's question bank.

• String: Expect manipulations, parsing, and validation. Master two-pointer techniques and sliding windows.
• Stack: Essential for parsing, validation (e.g., parentheses), and problems requiring LIFO logic, like evaluating expressions.
• Array: The foundation. Be proficient in traversal, in-place operations, and prefix sum techniques.
• Trie (Prefix Tree): A key differentiator for the Hard problems, crucial for efficient prefix-based search and storage.
• Math: Often involves number properties, modular arithmetic, or simulation-based problems derived from mathematical rules.

For the Trie, a top-tier topic for Hard problems, understanding the implementation is non-negotiable. Here is the core structure:

class TrieNode:
    def __init__(self):
        self.children = {}
        self.is_end_of_word = False

class Trie:
    def __init__(self):
        self.root = TrieNode()

    def insert(self, word: str) -> None:
        node = self.root
        for char in word:
            if char not in node.children:
                node.children[char] = TrieNode()
            node = node.children[char]
        node.is_end_of_word = True

    def search(self, word: str) -> bool:
        node = self.root
        for char in word:
            if char not in node.children:
                return False
            node = node.children[char]
        return node.is_end_of_word

    def startsWith(self, prefix: str) -> bool:
        node = self.root
        for char in prefix:
            if char not in node.children:
                return False
            node = node.children[char]
        return True

Preparation Strategy — A 4-6 Week Study Plan

A structured plan is essential to cover the breadth and depth required.

Weeks 1-2: Foundation & Core Topics

• Drill Easy problems on Arrays and Strings. Aim for speed and 100% correctness.
• Study Stack fundamentals. Solve ~15 classic problems (e.g., valid parentheses, min stack).
• Practice basic Math problems involving simulation and number theory.

Weeks 3-4: Advanced Data Structures & Pattern Recognition

• Dedicate significant time to Trie theory and implementation. Solve 5-10 Hard problems that utilize it.
• Revisit Arrays and Strings, but focus on Hard-level questions that combine these with other concepts.
• Start doing timed mock interviews focusing on a mix of Easy and Hard problems.

Weeks 5-6: Integration and Mock Interviews

• No new topics. Conduct at least 8-10 full mock interviews simulating Ericsson's format (e.g., one Easy followed by one Hard).
• Analyze every mistake. Was it a syntax error (Easy failure) or a flawed approach (Hard failure)?
• Re-implement your most challenging Trie and Stack solutions from memory.

Key Tips

1. Perfect Your Easy Game. Write code for simple problems as if it will go directly to production—impeccable readability, proper edge-case handling, and optimal space/time complexity from the start.
2. Communicate Your Trie Thought Process. When a Hard problem hints at prefixes (search, autocomplete), explicitly state, "This suggests a Trie could optimize the prefix search to O(prefix length)." Then implement it cleanly.
3. Practice Time Boxing. Allocate strict time limits: 12-15 minutes for an Easy, 30-35 for a Hard. If stuck, articulate a fallback brute-force approach before optimizing.
4. Test with Edge Cases. For String and Array problems, always test empty inputs, single-element inputs, and large, repetitive inputs verbally before declaring completion.
5. Master One Language. Use Python for speed, Java for type-explicit structure, or JavaScript for full-stack roles. Be deeply fluent in its standard library for your core topics.

Success with Ericsson's interview hinges on dual mastery: robotic precision on fundamentals and creative, structured problem-solving for high-complexity challenges. Target your practice accordingly.

Browse all Ericsson questions on CodeJeet