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).