Compute interval mode, BST range sum, exclusive time

You are given several independent coding tasks. ### A) Most frequent integer covered by intervals You are given an integer range `[-M, M]` and a list of inclusive integer intervals, e.g. `[1, 3]` means the integers `{1,2,3}` are each covered once by that interval. Multiple intervals may overlap. Return **any** integer in `[-M, M]` that has the **maximum total coverage count** (i.e., appears in the most intervals when expanded to integers). If multiple integers tie for the maximum, returning any one of them is fine. Clarify assumptions/constraints you need (e.g., size of `M`, number of intervals, endpoints within `[-M, M]`). --- ### B) Range sum on a BST + follow-up optimization Given the root of a Binary Search Tree (BST) and two integers `low` and `high`, return the **sum of all node values** `v` such that `low <= v <= high`. **Follow-up:** Suppose the tree is very large and you need to answer **many** queries with different `[low, high]` ranges. What preprocessing or data structure would you use to make queries faster? --- ### C) Exclusive execution time from logs There are `n` functions labeled `0..n-1`. You are given a list of logs in chronological order. Each log is a string formatted as: `"<functionId>:start:<timestamp>"` or `"<functionId>:end:<timestamp>"` - `start` means the function starts at that timestamp. - `end` means the function ends at that timestamp (inclusive). - Functions may be nested due to calls. Return an array `ans` of length `n` where `ans[i]` is the **exclusive time** spent in function `i` (time in `i` excluding time in any functions it calls). State any needed assumptions (e.g., timestamps are integers, single-threaded execution).