Solve sliding window, heap, DP, in-place tasks

You are given several LeetCode-style coding tasks. Implement each with the stated time/space goals and handle edge cases. ## 1) Sliding Window: longest substring with all distinct characters **Input:** a string `s` (ASCII or lowercase letters). **Output:** an integer: the maximum length of a contiguous substring of `s` that contains **no repeated characters**. **Constraints:** target time `O(n)`. --- ## 2) Heap / Top-K: k closest points **Input:** an integer `k` and an array of points `points`, where each point is `(x, y)`. **Output:** any ordering of the **k points** with smallest squared distance to the origin, `x^2 + y^2`. **Constraints:** must be `O(n log k)` time (and `O(k)` extra space besides output). --- ## 3) DP: minimum items to reach a target sum **Input:** an array of positive integers `values` (can reuse each value unlimited times) and an integer `amount`. **Output:** the minimum number of values needed to sum to `amount`; return `-1` if impossible. **Constraints:** explain state definition and initialization clearly; typical target `O(len(values) * amount)` time. --- ## 4) Sliding Window: find all anagram start indices **Input:** strings `s` and `p`. **Output:** all starting indices `i` such that `s[i : i+len(p)]` is a permutation of `p`. **Constraints:** target `O(|s|)` time using a fixed-size window and character counts. --- ## 5) Array in-place: previous permutation with one swap **Input:** an integer array `a`. **Output:** the lexicographically largest array that is **strictly smaller** than `a` and can be obtained by **at most one swap** of two indices. If no such array exists, return `a` unchanged. **Constraints:** in-place, `O(n)` or `O(n log n)`; clearly discuss corner cases (duplicates, already smallest permutation, repeated values near the pivot).