LeetCode Hot List: Course Schedule & Merge Intervals
Engineers deep in FAANG interview prep are highlighting the difficulty of specific LeetCode problems. One user shared their frustration with 'Course Schedule,' while another posted a #100DaysOfCode update tackling 'Merge Intervals' with brute force and optimized solutions. These problems appear to be common stumbling blocks in the current recruiting cycle.
'Course Schedule' iscloud.google.com/grounding-api-redirect/AUZIYQELAsBBFw9rPl5Kc0s5pY4_4VV935fM7N78KYv2EZyQaCvQowi9ltpUqX0F5RANjA7fOyt0hE-Y1wr0p2hJoQaLR3lavFNVuiszFGemYyQb03EaLFokGzgYjWcA_JzeVzSO_yFVrMkKG_Po0g==) fundamentally a graph theory problem that checks for cycles in a directed graph. Each course is a node, and a prerequisite is a directed edge; if a circular dependency exists, it's impossible to complete the schedule. This structure is analogous to real-world dependency tasks, from build systems to task scheduling. The standard solution to 'Course Schedule' involves a topological sort, which finds a linear ordering of nodes. This is typically implemented using either a Depth-First Search (DFS) or Breadth-First Search (BFS) algorithm to traverse the course dependencies and detect any cycles that would make a valid schedule impossible. 'Merge Intervals' tests a different skillset: handling array manipulation with a greedy algorithm. The problem requires combining all overlapping time periods from a given list into a set of mutually exclusive intervals. For example, the intervals and would merge to become. An optimal approach to 'Merge Intervals' has a time complexity of O(n log n), dominated by the initial step of sorting the intervals by their start times. Once sorted, a single pass is sufficient to merge overlapping periods by comparing the end of the previous interval with the start of the current one. Graph-based interview questions are common at FAANG companies because they test a candidate's ability to model ambiguous, real-world problems, not just their memorization of algorithms. They reveal how an engineer thinks when a problem doesn't look like a simple array or list. Both problems are classified as 'Medium' difficulty on LeetCode, a tier that interview candidates are often expected to solve within 25-40 minutes. 'Course Schedule' has been frequently asked in interviews at Amazon, Meta, and Google, while 'Merge Intervals' is a known staple at Meta, Amazon, Google, and Apple. The #100DaysOfCode challenge provides a structured and public way to practice such problems. The rules encourage coding for at least an hour daily and sharing progress on social media, creating a community of accountability for those in the midst of interview preparation.
