ByteDance QA Engineer Interview Questions

ByteDance aims to enhance video viewing experience by recommending similar videos based on user preferences. Given a directed graph where nodes represent videos and edges represent user preferences, apply DFS to find all reachable videos from a starting video node.
You need to implement the following function:

• List<Integer> recommendVideos(int[][] graph, int startVideo) - returns a list of all videos reachable from startVideo.

Example 1:
Input: graph = [[1, 2], [3], [3], []], startVideo = 0
Output: [1, 2, 3]
Explanation: From video 0, you can reach videos 1, 2, and 3.
Example 2:
Input: graph = [[1], [2], []], startVideo = 1
Output: [2]
Constraints:

• 0 <= graph.length <= 100


• 0 <= graph[i].length <= 100

In ByteDance’s video application, we need a system to filter video playlists based on user history. The goal is to maximize the number of unique videos in the playlist while adhering to a maximum length constraint.
You are given an int[] videoIds representing the videos a user has viewed and an int maxLength which is the maximum length that the playlist can be.
The function signature is:

• List<Integer> filterPlaylist(int[] videoIds, int maxLength) - returns a list of video IDs in the filtered playlist avoiding repetition.

Example 1:
Input: videoIds = [1, 2, 3, 1, 2, 3], maxLength = 4
Output: [1, 2, 3]
Explanation: The unique videos that fit within the length 4 are 1, 2, and 3.
Example 2:
Input: videoIds = [5, 6, 5, 7, 8, 6], maxLength = 5
Output: [5, 6, 7, 8]
Explanation: The unique videos that fit within the length 5 are 5, 6, 7, and 8.
Constraints:

• 0 <= videoIds.length <= 10000


• 1 <= maxLength <= 1000