LeetCode Interview Hot List Emerges
Specific LeetCode problems are trending in Big Tech interviews, signaling key areas of focus for companies. "Best Time to Buy and Sell Stock" (LC 121) is being used to test algorithmic thinking for fintech and trading systems. Meanwhile, "Serialize and Deserialize Binary Tree" (LC 297) is a go-to for assessing foundational backend and distributed systems knowledge.
Big Tech companies adopted algorithm-focused platforms to manage a high volume of applicants, creating a standardized way to filter for coding proficiency and problem-solving ability in a short timeframe. This approach is viewed as more meritocratic than relying on university prestige, as it provides a path for candidates from non-traditional backgrounds to demonstrate their skills. The "Best Time to Buy and Sell Stock" problem is a classic test of efficiency, challenging candidates to move beyond a simple but slow brute-force solution to a linear time O(n) algorithm. It specifically evaluates the use of greedy algorithms, where the optimal solution is built by making the best possible choice at each step, such as always tracking the lowest stock price found so far. "Serialize and Deserialize Binary Tree" tests concepts fundamental to building distributed systems, where complex data objects must be converted into a format suitable for network transmission or persistent storage. A successful solution requires a deep understanding of tree traversal algorithms (like pre-order or level-order) to ensure the structure can be perfectly reconstructed. The skills demonstrated in the serialization problem are a gateway to system design interviews, which are increasingly common for even junior-level roles. These interviews assess a candidate's ability to architect scalable systems by considering components like load balancing, caching, and database selection. To showcase backend and distributed systems knowledge, a portfolio can include projects like building a RESTful API with user authentication, creating a simple e-commerce platform with payment processing, or developing a file management service that interfaces with cloud storage like AWS S3. While algorithm platforms are central to interview prep, the industry is seeing a shift. Companies are increasingly using take-home projects and code review exercises to better simulate on-the-job tasks and get a more holistic view of a candidate's practical skills.
