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Problem solution · C++

K Th Smallest Remaining Even Integer in Subarray Queries

K Th Smallest Remaining Even Integer in Subarray Queries: a C++ solution using binary search. Learn the idea, check the complexity, and read the full code, with credit to Kamyu LeetCode Solutions.

Technique
Binary search
Source
Kamyu LeetCode Solutions
Length
35 lines
Start with the idea.

Try the problem first. If you get stuck, read the approach below, then write your own solution. The full code is at the bottom.

Approach

Binary search

For K Th Smallest Remaining Even Integer in Subarray Queries, the implementation exploits a monotonic condition to discard half of the remaining search space after every check.

  1. Identify the ordered answer range or sorted search domain.
  2. Write a predicate whose truth changes only once.
  3. Move the appropriate boundary after each midpoint check and return the final feasible position.

Code notes

  • 35 lines of C++ from the credited upstream file k-th-smallest-remaining-even-integer-in-subarray-queries.cpp.
  • The implementation visibly relies on sequence storage.
  • 3 loop blocks detected.

Complexity

Multiply the logarithmic number of midpoint checks by the cost of one predicate evaluation.

Check the problem constraints before deciding whether this complexity will pass.

Source

Code and credit

This code comes from Kamyu LeetCode Solutions by kamyu104 and is used under the MIT licence.

Open problem ↗Original source ↗
Full codeK Th Smallest Remaining Even Integer in Subarray Queries · C++C++
Use this to learn the idea, then write your own version.
// Time:  O(n + qlogn)// Space: O(n) // prefix sum, binary searchclass Solution {public:    vector<int> kthRemainingInteger(vector<int>& nums, vector<vector<int>>& queries) {        const auto& binary_search_right = [](int left, int right, const auto& check) {            while (left <= right) {                int mid = left + (right - left) / 2;                if (!check(mid)) {                    right = mid - 1;                } else {                    left = mid + 1;                }            }            return right;        };         vector<int> prefix(size(nums) + 1);        for (int i = 0; i < size(nums); ++i) {            prefix[i + 1] = prefix[i] + (nums[i] % 2 == 0 ? 1 : 0);        }        vector<int> result(size(queries));        for (int i = 0; i < size(queries); ++i) {            const auto& l = queries[i][0], &r = queries[i][1], &k = queries[i][2];            const auto& j = binary_search_right(l, r, [&](int x) {                return nums[x] / 2 < k + (prefix[x + 1] - prefix[l]);            });            result[i] = 2 * (k + (prefix[j + 1] - prefix[l]));        }        return result;    }};

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