Juniper Networks Coding Interview Questions
25 Juniper Networks coding interview problems with full optimal solutions — 8 easy, 12 medium, 5 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Juniper Networks interviewer values, and a FAQ section.
Showing 12 problems of 25
- #3mediumvery frequently asked
3. Longest Substring Without Repeating Characters
Find the length of the longest substring with all unique characters using a sliding window. Juniper asks this because sliding-window packet inspection — maintaining a window of unique protocol tokens in a byte stream without rescanning — is a real pattern in deep-packet-inspection engines.
- #15mediumfrequently asked
15. 3Sum
Find all unique triplets that sum to zero. Juniper uses 3Sum to test whether candidates can compose sort + two-pointer cleanly and handle duplicate elimination — the same multi-pass filtering logic appears in prefix-list deduplication and routing policy intersection in network management software.
- #49mediumsometimes asked
49. Group Anagrams
Group strings that are anagrams of each other. Juniper uses this to test canonical-key hashing — the same pattern appears when normalizing and grouping interface configuration commands that differ only in token order before feeding them to a configuration management pipeline.
- #56mediumfrequently asked
56. Merge Intervals
Merge overlapping intervals into a minimal set. Juniper asks this because merging overlapping prefix ranges is a real task in IP route aggregation — combining contiguous or overlapping CIDR blocks into a shorter routing table is exactly this algorithm applied to network address space.
- #139mediumsometimes asked
139. Word Break
Determine whether a string can be segmented into words from a dictionary using dynamic programming. Juniper asks this in software roles because tokenizing CLI command strings and configuration keywords against a known vocabulary — exactly the problem Junos CLI parsing faces — maps directly to this DP structure.
- #146mediumvery frequently asked
146. LRU Cache
Design an O(1) LRU cache backed by a hash map and doubly-linked list. Juniper's Junos control plane caches route lookups and ARP entries with eviction policies — an LRU cache is a real data structure used in forwarding table management, making this a high-signal design-meets-coding problem.
- #200mediumvery frequently asked
200. Number of Islands
Count connected components in a 2D grid using BFS or DFS. Juniper asks this because connected-component analysis in graphs is the foundation of network topology discovery — finding isolated subnetworks, counting autonomous systems reachable from a border router, and flood-fill-based link-state calculation all follow this pattern.
- #207mediumfrequently asked
207. Course Schedule
Detect a cycle in a directed graph to determine if courses can be completed. Juniper maps this directly to dependency resolution in Junos package management and routing protocol initialization — if module A requires B which requires A, the system deadlocks. Topological cycle detection is a core systems skill.
- #236mediumsometimes asked
236. Lowest Common Ancestor of a Binary Tree
Find the lowest common ancestor of two nodes in a binary tree using recursive post-order traversal. Juniper applies this to hierarchical network configuration trees — finding the most-specific policy node that governs both a source and destination interface requires exactly this LCA traversal.
- #238mediumsometimes asked
238. Product of Array Except Self
Return an array where each element is the product of all other elements, without using division. Juniper tests this because the left-right prefix scan pattern appears in networking contexts like computing per-interface cumulative traffic without a global total — the trick of two passes is a systems-thinking insight.
- #322mediumfrequently asked
322. Coin Change
Find the minimum number of coins to make a target amount. Juniper uses this classic DP problem to test unbounded knapsack thinking — the same minimum-cost path logic applies to finding the minimum number of hops or minimum-cost route segments in a shortest-path calculation on a weighted network.
- #347mediumfrequently asked
347. Top K Frequent Elements
Return the k most frequent elements in an array. Juniper asks this in control-plane and telemetry roles where finding the top-k most-seen BGP prefixes, OSPF neighbors, or interface error codes in a data stream is a real operational problem — it tests both counting and efficient selection.