Data Structures & Algorithms Interview Prep: The Complete Guide
This guide covers the data structures and algorithms patterns that appear most frequently in software engineering interviews at top companies — with the specific patterns that matter most.
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Arrays and Strings
Two Pointers: use when you need to find pairs or sub-arrays matching a condition. Sliding Window: use for max/min/subarray problems with a constraint. Prefix Sum: use when asked about range sum queries. Common problems: 3Sum, Minimum Window Substring, Maximum Subarray.
HashMaps and Sets
The single most common interview data structure. Use for O(1) lookup, frequency counting, and de-duplication. Two Sum is the canonical hashmap problem — but the pattern appears in Subarray Sum Equals K, Group Anagrams, Top K Frequent Elements.
Trees and Graphs
Know recursive DFS and iterative BFS cold. For trees: in-order traversal gives sorted output for BSTs. For graphs: BFS for shortest path (unweighted), DFS for connectivity. Must-know: Lowest Common Ancestor, Binary Tree Maximum Path Sum, Course Schedule (topological sort).
Dynamic Programming
Most interview DP comes down to: define the state, write the recurrence, handle base cases. Common patterns: 0/1 knapsack (include or skip), longest common subsequence, interval DP. Start with brute-force recursion, then memoize, then convert to tabulation if needed.
Sorting and Searching
Know merge sort and quicksort conceptually. For interviews, the key skill is binary search variations: search on sorted rotated array, find first/last position, binary search on the answer space (Koko Eating Bananas, Capacity to Ship Packages).
Time and Space Complexity
Every interview solution needs a complexity analysis. Practice stating it before the interviewer asks. Common patterns: O(n log n) usually means sorting. O(n) usually means a single pass with auxiliary data structure. O(n²) usually means nested loops — often a hint to optimize.
Key Takeaways
- →Learn the patterns, not the problems — there are ~15 patterns that cover 90% of interview problems
- →Write clean code: good variable names, modular functions, edge case handling
- →Always discuss trade-offs: "This is O(n) space — we could reduce it to O(1) by..."