方法1: DP

首先还是需要对pairs的right进行排序。一方面是为了方便chaining，另一方面是可以去重。

然后定义 dp[i] := 以pairs[i]作为结尾，最长的序列的长度。

状态转移：dp[i] = max(dp[j] + 1) where pairs[i].left > pairs[j].right and 0 < j < i.

解释：对于pairs[i]，找一个最优的pairs[j]，满足pairs[i].left > pairs[j].right，这样我就可以把pairs[i]追加到以pairs[j]结尾的最长序列后面了，长度+1。

边检条件：dp[0:n] = 1，每个pair以自己作为序列的最后元素，长度为1。

时间复杂度：O(n²)
空间复杂度：O(n)

class Solution {
public:
  int findLongestChain(vector<vector<int>>& pairs) {
    sort(begin(pairs), end(pairs), [](const auto& p1, const auto& p2){
      return p1[1] < p2[1];
    });

    const int n = pairs.size();

    vector<int> dp(n, 1);
    for (int i = 0; i < n; ++i)
      for (int j = 0; j < i; ++j)
        if (pairs[i][0] > pairs[j][1])
          dp[i] = max(dp[i], dp[j] + 1);

    return *max_element(begin(dp), end(dp));
  }
};

方法2: 贪心

和DP一样，对数据进行排序。

每当我看到 cur.left > prev.right，那么就直接把cur接在prev后面。我们需要证明这么做是最优的，而不是跳过它选后面的元素。

Case 0: cur已经是最后一个元素了，跳过就不是最优解了。

假设cur后面有next, 因为已经排序过了，我们可以得知 next.right >= cur.right。

Case 1: next.right == cur.right。这时候选cur和选next对后面的决策来说是一样的，但由于Case 0的存在，我必须选cur。

Case 2: next.right > cur.right。不管left的情况怎么样，由于right更小，这时候选择cur一定是优于next。

综上所述，看到有元素可以连接起来就贪心的选它就对了。

时间复杂度：O(nlogn)
空间复杂度：O(1)

class Solution {
public:
  int findLongestChain(vector<vector<int>>& pairs) {
    sort(begin(pairs), end(pairs), [](const auto& p1, const auto& p2){
      return p1[1] < p2[1];
    });

    int right = INT_MIN;
    int ans = 0;
    for (const auto& p : pairs)
      if (p[0] > right) {
        right = p[1];
        ++ans;
      }
    return ans;
  }
};

An array of distinct positive integers is called a k-avoiding array if there does not exist any pair of distinct elements that sum to k.

Return the minimum possible sum of a k-avoiding array of length n.

Example 1:

Input: n = 5, k = 4
Output: 18
Explanation: Consider the k-avoiding array [1,2,4,5,6], which has a sum of 18.
It can be proven that there is no k-avoiding array with a sum less than 18.

Example 2:

Input: n = 2, k = 6
Output: 3
Explanation: We can construct the array [1,2], which has a sum of 3.
It can be proven that there is no k-avoiding array with a sum less than 3.

Constraints:

• 1 <= n, k <= 50

Solution 1: Greedy + HashTable

Always choose the smallest possible number starting from 1.

Add all chosen numbers into a hashtable. For a new candidate i, check whether k – i is already in the hashtable.

Time complexity: O(n)
Space complexity: O(n)

// Author: Huahua
class Solution {
public:
  int minimumSum(int n, int k) {    
    int sum = 0;
    unordered_set<int> s;
    for (int i = 1; s.size() != n; ++i) {
      if (s.count(k - i)) continue;
      sum += i;
      s.insert(i);
    }
    return sum;
  }
};

An integer x is called achievable if it can become equal to num after applying the following operation no more than t times:

• Increase or decrease x by 1, and simultaneously increase or decrease num by 1.

Return the maximum possible achievable number. It can be proven that there exists at least one achievable number.

Example 1:

Input: num = 4, t = 1
Output: 6
Explanation: The maximum achievable number is x = 6; it can become equal to num after performing this operation:
1- Decrease x by 1, and increase num by 1. Now, x = 5 and num = 5. 
It can be proven that there is no achievable number larger than 6.

Example 2:

Input: num = 3, t = 2
Output: 7
Explanation: The maximum achievable number is x = 7; after performing these operations, x will equal num: 
1- Decrease x by 1, and increase num by 1. Now, x = 6 and num = 4.
2- Decrease x by 1, and increase num by 1. Now, x = 5 and num = 5.
It can be proven that there is no achievable number larger than 7.

Constraints:

• 1 <= num, t <= 50

Solution: Greedy

Always decrease x and always increase num, the max achievable number x = num + t * 2

Time complexity: O(1)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int theMaximumAchievableX(int num, int t) {
    return num + t * 2;
  }
};

1. Select an element m from nums.
2. Remove the selected element m from the array.
3. Add a new element with a value of m + 1 to the array.
4. Increase your score by m.

Return the maximum score you can achieve after performing the operation exactly k times.

Example 1:

Input: nums = [1,2,3,4,5], k = 3
Output: 18
Explanation: We need to choose exactly 3 elements from nums to maximize the sum.
For the first iteration, we choose 5. Then sum is 5 and nums = [1,2,3,4,6]
For the second iteration, we choose 6. Then sum is 5 + 6 and nums = [1,2,3,4,7]
For the third iteration, we choose 7. Then sum is 5 + 6 + 7 = 18 and nums = [1,2,3,4,8]
So, we will return 18.
It can be proven, that 18 is the maximum answer that we can achieve.

Example 2:

Input: nums = [5,5,5], k = 2
Output: 11
Explanation: We need to choose exactly 2 elements from nums to maximize the sum.
For the first iteration, we choose 5. Then sum is 5 and nums = [5,5,6]
For the second iteration, we choose 6. Then sum is 5 + 6 = 11 and nums = [5,5,7]
So, we will return 11.
It can be proven, that 11 is the maximum answer that we can achieve.

Constraints:

• 1 <= nums.length <= 100
• 1 <= nums[i] <= 100
• 1 <= k <= 100

Solution: Greedy

Always to chose the largest element from the array.

We can find the largest element of the array m, then the total score will be
m + (m + 1) + (m + 2) + … + (m + k – 1),
We can use summation formula of arithmetic sequence to compute that in O(1)
ans = (m + (m + k – 1)) * k / 2

Time complexity: O(n)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int maximizeSum(vector<int>& nums, int k) {
    int m = *max_element(begin(nums), end(nums));
    return (m + m + k - 1) * k / 2;
  }
};

Let prefix be the array containing the prefix sums of nums after rearranging it. In other words, prefix[i] is the sum of the elements from 0 to i in nums after rearranging it. The score of nums is the number of positive integers in the array prefix.

Return the maximum score you can achieve.

Example 1:

Input: nums = [2,-1,0,1,-3,3,-3]
Output: 6
Explanation: We can rearrange the array into nums = [2,3,1,-1,-3,0,-3].
prefix = [2,5,6,5,2,2,-1], so the score is 6.
It can be shown that 6 is the maximum score we can obtain.

Example 2:

Input: nums = [-2,-3,0]
Output: 0
Explanation: Any rearrangement of the array will result in a score of 0.

Constraints:

• 1 <= nums.length <= 105
• -106 <= nums[i] <= 106

Solution: Greedy

Sort the numbers in descending order.

Time complexity: O(nlogn)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int maxScore(vector<int>& nums) {
    sort(rbegin(nums), rend(nums));
    int ans = 0;
    for (long i = 0, s = 0; i < nums.size(); ++i) {
      s += nums[i];
      if (s <= 0) break;
      ++ans;
    }
    return ans;
  }
};

• The chosen integers have to be in the range [1, n].
• Each integer can be chosen at most once.
• The chosen integers should not be in the array banned.
• The sum of the chosen integers should not exceed maxSum.

Return the maximum number of integers you can choose following the mentioned rules.

Example 1:

Input: banned = [1,6,5], n = 5, maxSum = 6
Output: 2
Explanation: You can choose the integers 2 and 4.
2 and 4 are from the range [1, 5], both did not appear in banned, and their sum is 6, which did not exceed maxSum.

Example 2:

Input: banned = [1,2,3,4,5,6,7], n = 8, maxSum = 1
Output: 0
Explanation: You cannot choose any integer while following the mentioned conditions.

Example 3:

Input: banned = [11], n = 7, maxSum = 50
Output: 7
Explanation: You can choose the integers 1, 2, 3, 4, 5, 6, and 7.
They are from the range [1, 7], all did not appear in banned, and their sum is 28, which did not exceed maxSum.

Constraints:

• 1 <= banned.length <= 104
• 1 <= banned[i], n <= 104
• 1 <= maxSum <= 109

Solution 1: Greedy + HashSet

We would like to use the smallest numbers possible. Store all the banned numbers into a hashset, and enumerate numbers from 1 to n and check whether we can use that number.

Time complexity: O(m + n)
Space complexity: O(m)

// Author: Huahua
class Solution {
public:
  int maxCount(vector<int>& banned, int n, int maxSum) {
    unordered_set<int> m(begin(banned), end(banned));
    int ans = 0;    
    for (int i = 1, j = 0, sum = 0; i <= n; ++i) {
      if (sum + i > maxSum) break;
      if (m.count(i)) continue;
      sum += i;
      ++ans;
    }
    return ans;
  }
};

Solution 2: Two Pointers

Sort the banned numbers. Use one pointer j and compare with the current number i.

Time complexity: O(mlogm + n)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int maxCount(vector<int>& banned, int n, int maxSum) {
    sort(begin(banned), end(banned));
    int ans = 0;    
    for (int i = 1, j = 0, sum = 0; i <= n; ++i) {
      if (sum + i > maxSum) break;
      while (j < banned.size() && banned[j] < i) ++j;
      if (j < banned.size() && i == banned[j]) continue;
      sum += i;
      ++ans;
    }
    return ans;
  }
};

There is a meeting for the representatives of each city. The meeting is in the capital city.

There is a car in each city. You are given an integer seats that indicates the number of seats in each car.

A representative can use the car in their city to travel or change the car and ride with another representative. The cost of traveling between two cities is one liter of fuel.

Return the minimum number of liters of fuel to reach the capital city.

Example 1:

Input: roads = [[0,1],[0,2],[0,3]], seats = 5
Output: 3
Explanation: 
- Representative1 goes directly to the capital with 1 liter of fuel.
- Representative2 goes directly to the capital with 1 liter of fuel.
- Representative3 goes directly to the capital with 1 liter of fuel.
It costs 3 liters of fuel at minimum. 
It can be proven that 3 is the minimum number of liters of fuel needed.

Example 2:

Input: roads = [[3,1],[3,2],[1,0],[0,4],[0,5],[4,6]], seats = 2
Output: 7
Explanation: 
- Representative2 goes directly to city 3 with 1 liter of fuel.
- Representative2 and representative3 go together to city 1 with 1 liter of fuel.
- Representative2 and representative3 go together to the capital with 1 liter of fuel.
- Representative1 goes directly to the capital with 1 liter of fuel.
- Representative5 goes directly to the capital with 1 liter of fuel.
- Representative6 goes directly to city 4 with 1 liter of fuel.
- Representative4 and representative6 go together to the capital with 1 liter of fuel.
It costs 7 liters of fuel at minimum. 
It can be proven that 7 is the minimum number of liters of fuel needed.

Example 3:

Input: roads = [], seats = 1
Output: 0
Explanation: No representatives need to travel to the capital city.

Constraints:

• 1 <= n <= 105
• roads.length == n - 1
• roads[i].length == 2
• 0 <= ai, bi < n
• ai != bi
• roads represents a valid tree.
• 1 <= seats <= 105

Solution: Greedy + DFS

To reach the minimum cost, we must share cars if possible, say X reps from children nodes to an intermediate node u on the way towards capital 0. Then they all changes cars at node u, and we need (X + 1) // seats cars/fuel from u to 0.

We use DFS to count # of reps at each node u while accumulating the total cost.

Time complexity: O(n)
Space complexity: O(n)

// Author: Huahua
class Solution {
public:
  long long minimumFuelCost(vector<vector<int>>& roads, int seats) {
    long long ans = 0;
    vector<vector<int>> g(roads.size() + 1);
    for (const vector<int>& r : roads) {
      g[r[0]].push_back(r[1]);
      g[r[1]].push_back(r[0]);
    }
    // Returns total # of children of u.
    function<int(int, int)> dfs = [&](int u, int p, int rep = 1) {      
      for (int v : g[u])
        if (v != p) rep += dfs(v, u);
      if (u) ans += (rep + seats - 1) / seats;
      return rep;
    };
    dfs(0, -1);
    return ans;
  }
};

Consider a non-empty subarray from nums that has the maximum possible bitwise AND.

• In other words, let k be the maximum value of the bitwise AND of any subarray of nums. Then, only subarrays with a bitwise AND equal to k should be considered.

Return the length of the longest such subarray.

The bitwise AND of an array is the bitwise AND of all the numbers in it.

A subarray is a contiguous sequence of elements within an array.

Example 1:

Input: nums = [1,2,3,3,2,2]
Output: 2
Explanation:
The maximum possible bitwise AND of a subarray is 3.
The longest subarray with that value is [3,3], so we return 2.

Example 2:

Input: nums = [1,2,3,4]
Output: 1
Explanation:
The maximum possible bitwise AND of a subarray is 4.
The longest subarray with that value is [4], so we return 1.

Constraints:

• 1 <= nums.length <= 105
• 1 <= nums[i] <= 106

Solution: Find the largest number

a & b <= a
a & b <= b
if b > a, a & b < b, we choose to start a new sequence of “b” instead of continuing with “ab”

Basically, we find the largest number in the array and count the longest sequence of it. Note, there will be some tricky cases like.
b b b b a b
b a b b b b
We need to return 4 instead of 1.

Time complexity: O(n)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int longestSubarray(vector<int>& nums) {
    int ans = 0;
    int best = 0;
    for (int i = 0, l = 0; i < nums.size(); ++i) {
      if (nums[i] > best) {
        best = nums[i]; 
        ans = l = 1;
      } else if (nums[i] == best) {
        ans = max(ans, ++l);
      } else {
        l = 0;
      }
    }    
    return ans;
  }
};

Given a string s, partition the string into one or more substrings such that the characters in each substring are unique. That is, no letter appears in a single substring more than once.

Return the minimum number of substrings in such a partition.

Note that each character should belong to exactly one substring in a partition.

Example 1:

Input: s = "abacaba"
Output: 4
Explanation:
Two possible partitions are ("a","ba","cab","a") and ("ab","a","ca","ba").
It can be shown that 4 is the minimum number of substrings needed.

Example 2:

Input: s = "ssssss"
Output: 6
Explanation:
The only valid partition is ("s","s","s","s","s","s").

Constraints:

• 1 <= s.length <= 105
• s consists of only English lowercase letters.

Solution: Greedy

Extend the cur string as long as possible unless a duplicate character occurs.

You can use hashtable / array or bitmask to mark whether a character has been seen so far.

Time complexity: O(n)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int partitionString(string s) {
    unordered_set<char> m;
    int ans = 0;
    for (char c : s) {
      if (m.insert(c).second) continue;
      m.clear();
      m.insert(c);
      ++ans;
    }
    return ans + 1;
  }
};

// Author: Huahua
class Solution {
public:
  int partitionString(string s) {
    vector<int> m(26);
    int ans = 0;
    for (char c : s) {
      if (++m[c - 'a'] == 1) continue;
      fill(begin(m), end(m), 0);
      m[c - 'a'] = 1;
      ++ans;
    }
    return ans + 1;
  }
};

// Author: Huahua
class Solution {
public:
  int partitionString(string s) {
    int mask = 0;
    int ans = 0;
    for (char c : s) {
      if (mask & (1 << (c - 'a'))) {
        mask = 0;        
        ++ans;
      }
      mask |= 1 << (c - 'a');
    }
    return ans + 1;
  }
};

You are given a 0-indexed integer array scores of length n where scores[i] denotes the score of node i. You are also given a 2D integer array edges where edges[i] = [ai, bi] denotes that there exists an undirected edge connecting nodes ai and bi.

A node sequence is valid if it meets the following conditions:

• There is an edge connecting every pair of adjacent nodes in the sequence.
• No node appears more than once in the sequence.

The score of a node sequence is defined as the sum of the scores of the nodes in the sequence.

Return the maximum score of a valid node sequence with a length of 4. If no such sequence exists, return -1.

Example 1:

Input: scores = [5,2,9,8,4], edges = [[0,1],[1,2],[2,3],[0,2],[1,3],[2,4]]
Output: 24
Explanation: The figure above shows the graph and the chosen node sequence [0,1,2,3].
The score of the node sequence is 5 + 2 + 9 + 8 = 24.
It can be shown that no other node sequence has a score of more than 24.
Note that the sequences [3,1,2,0] and [1,0,2,3] are also valid and have a score of 24.
The sequence [0,3,2,4] is not valid since no edge connects nodes 0 and 3.

Example 2:

Input: scores = [9,20,6,4,11,12], edges = [[0,3],[5,3],[2,4],[1,3]]
Output: -1
Explanation: The figure above shows the graph.
There are no valid node sequences of length 4, so we return -1.

Constraints:

• n == scores.length
• 4 <= n <= 5 * 104
• 1 <= scores[i] <= 108
• 0 <= edges.length <= 5 * 104
• edges[i].length == 2
• 0 <= ai, bi <= n - 1
• ai != bi
• There are no duplicate edges.

Solution: Greedy / Top3 neighbors

Since |E| is already 5*10⁴, we can’t enumerate all possible sequences. We must do in O(|E|) or O(|E|log|E|).

Enumerate all the edges, we have a pair of node a, b. To get the optimal answer, we just need to find the largest neighbor of a and b, which we call c, d respectively. Just need to make sure a, b, c, d are unique. i.e. c != d, c != b and d != a. Since the a’s largest neighbor can be either b or d. We can’t just store the largest neighbor, but top 3 instead for each node to avoid duplications.

Time complexity: O(|E|*9)
Space complexity: O(|V|*3)

// Author: Huahua
class Solution {
public:
  int maximumScore(vector<int>& scores, vector<vector<int>>& edges) {
    const int n = scores.size();
    vector<set<pair<int, int>>> top3(n);
    for (const auto& e : edges) {      
      top3[e[0]].emplace(scores[e[1]], e[1]);
      top3[e[1]].emplace(scores[e[0]], e[0]);
      if (top3[e[0]].size() > 3) top3[e[0]].erase(begin(top3[e[0]]));
      if (top3[e[1]].size() > 3) top3[e[1]].erase(begin(top3[e[1]]));
    }
    int ans = -1;
    for (const auto& e : edges) {
      const int a = e[0], b = e[1], sa = scores[a], sb = scores[b];
      for (const auto& [sc, c] : top3[a])
        for (const auto& [sd, d] : top3[b])          
          if (sa + sb + sc + sd > ans && c != b && c != d && d != a)
            ans = sa + sb + sc + sd;
    }
    return ans;
  }
};

Return the maximum product of nums after at most k operations. Since the answer may be very large, return it modulo 109 + 7.

Example 1:

Input: nums = [0,4], k = 5
Output: 20
Explanation: Increment the first number 5 times.
Now nums = [5, 4], with a product of 5 * 4 = 20.
It can be shown that 20 is maximum product possible, so we return 20.
Note that there may be other ways to increment nums to have the maximum product.

Example 2:

Input: nums = [6,3,3,2], k = 2
Output: 216
Explanation: Increment the second number 1 time and increment the fourth number 1 time.
Now nums = [6, 4, 3, 3], with a product of 6 * 4 * 3 * 3 = 216.
It can be shown that 216 is maximum product possible, so we return 216.
Note that there may be other ways to increment nums to have the maximum product.

Constraints:

• 1 <= nums.length, k <= 105
• 0 <= nums[i] <= 106

Solution: priority queue

Always increment the smallest number. Proof?

Time complexity: O(klogn + nlogn)
Space complexity: O(n)

// Author: Huahua
class Solution {
public:
  int maximumProduct(vector<int>& nums, int k) {
    constexpr int kMod = 1e9 + 7;
    priority_queue<int, vector<int>, greater<int>> q(begin(nums), end(nums));
    while (k--) {
      const int n = q.top(); 
      q.pop();
      q.push(n + 1);
    }
    long long ans = 1;
    while (!q.empty()) {
      ans *= q.top(); q.pop();
      ans %= kMod;
    }
    return ans;
  }
};

24-hour times are formatted as "HH:MM", where HH is between 00 and 23, and MM is between 00 and 59. The earliest 24-hour time is 00:00, and the latest is 23:59.

In one operation you can increase the time current by 1, 5, 15, or 60 minutes. You can perform this operation any number of times.

Return the minimum number of operations needed to convert current to correct.

Example 1:

Input: current = "02:30", correct = "04:35"
Output: 3
Explanation:
We can convert current to correct in 3 operations as follows:
- Add 60 minutes to current. current becomes "03:30".
- Add 60 minutes to current. current becomes "04:30".
- Add 5 minutes to current. current becomes "04:35".
It can be proven that it is not possible to convert current to correct in fewer than 3 operations.

Example 2:

Input: current = "11:00", correct = "11:01"
Output: 1
Explanation: We only have to add one minute to current, so the minimum number of operations needed is 1.

Constraints:

• current and correct are in the format "HH:MM"
• current <= correct

Solution: Greedy

Start with 60, then 15, 5 and finally increase 1 minute a time.

Time complexity: O(1)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  int convertTime(string current, string correct) {
    auto getMinute = [](string_view t) {
      return (t[0] - '0') * 10 * 60 
             + (t[1] - '0') * 60 
             + (t[3] - '0') * 10 
             + (t[4] - '0');
    };
    
    int t1 = getMinute(current);
    int t2 = getMinute(correct);
    int ans = 0;    
    for (int d : {60, 15, 5, 1})
      while (t2 - t1 >= d) {
        ++ans;
        t1 += d;
      }
    return ans;
  }
};

Return the minimum number of operations to reduce the sum of nums by at least half.

Example 1:

Input: nums = [5,19,8,1]
Output: 3
Explanation: The initial sum of nums is equal to 5 + 19 + 8 + 1 = 33.
The following is one of the ways to reduce the sum by at least half:
Pick the number 19 and reduce it to 9.5.
Pick the number 9.5 and reduce it to 4.75.
Pick the number 8 and reduce it to 4.
The final array is [5, 4.75, 4, 1] with a total sum of 5 + 4.75 + 4 + 1 = 14.75. 
The sum of nums has been reduced by 33 - 14.75 = 18.25, which is at least half of the initial sum, 18.25 >= 33/2 = 16.5.
Overall, 3 operations were used so we return 3.
It can be shown that we cannot reduce the sum by at least half in less than 3 operations.

Example 2:

Input: nums = [3,8,20]
Output: 3
Explanation: The initial sum of nums is equal to 3 + 8 + 20 = 31.
The following is one of the ways to reduce the sum by at least half:
Pick the number 20 and reduce it to 10.
Pick the number 10 and reduce it to 5.
Pick the number 3 and reduce it to 1.5.
The final array is [1.5, 8, 5] with a total sum of 1.5 + 8 + 5 = 14.5. 
The sum of nums has been reduced by 31 - 14.5 = 16.5, which is at least half of the initial sum, 16.5 >= 31/2 = 16.5.
Overall, 3 operations were used so we return 3.
It can be shown that we cannot reduce the sum by at least half in less than 3 operations.

Constraints:

• 1 <= nums.length <= 105
• 1 <= nums[i] <= 107

Solution: Greedy + PriorityQueue/Max Heap

Always half the largest number, put all the numbers onto a max heap (priority queue), extract the largest one, and put reduced number back.

Time complexity: O(nlogn)
Space complexity: O(n)

// Author: Huahua
class Solution {
public:
  int halveArray(vector<int>& nums) {
    double sum = accumulate(begin(nums), end(nums), 0.0);
    priority_queue<double> q;
    for (int num : nums) q.push(num);
    int ans = 0;
    for (double cur = sum; cur > sum / 2; ++ans) {    
      double num = q.top(); q.pop();
      cur -= num / 2;
      q.push(num / 2);
    }
    return ans;
  }
};

Return the sum of the k integers appended to nums.

Example 1:

Input: nums = [1,4,25,10,25], k = 2
Output: 5
Explanation: The two unique positive integers that do not appear in nums which we append are 2 and 3.
The resulting sum of nums is 1 + 4 + 25 + 10 + 25 + 2 + 3 = 70, which is the minimum.
The sum of the two integers appended is 2 + 3 = 5, so we return 5.

Example 2:

Input: nums = [5,6], k = 6
Output: 25
Explanation: The six unique positive integers that do not appear in nums which we append are 1, 2, 3, 4, 7, and 8.
The resulting sum of nums is 5 + 6 + 1 + 2 + 3 + 4 + 7 + 8 = 36, which is the minimum. 
The sum of the six integers appended is 1 + 2 + 3 + 4 + 7 + 8 = 25, so we return 25.

Constraints:

• 1 <= nums.length <= 105
• 1 <= nums[i] <= 109
• 1 <= k <= 108

Solution: Greedy + Math, fill the gap

Sort all the numbers and remove duplicated ones, and fill the gap between two neighboring numbers.
e.g. [15, 3, 8, 8] => sorted = [3, 8, 15]
fill 0->3, 1,2, sum = ((0 + 1) + (3-1)) * (3-0-1) / 2 = 3
fill 3->8, 4, 5, 6, 7, sum = ((3 + 1) + (8-1)) * (8-3-1) / 2 = 22
fill 8->15, 9, 10, …, 14, …
fill 15->inf, 16, 17, …

Time complexity: O(nlogn)
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  long long minimalKSum(vector<int>& nums, int k) {    
    sort(begin(nums), end(nums));
    long long ans = 0;
    long long p = 0;
    for (int c : nums) {
      if (c == p) continue;
      long long n = min((long long)k, c - p - 1);
      ans += (p + 1 + p + n) * n / 2; 
      k -= n;
      p = c;
    }
    ans += (p + 1 + p + k) * k / 2;
    return ans;
  }
};

• For example, given finalSum = 12, the following splits are valid (unique positive even integers summing up to finalSum): (12), (2 + 10), (2 + 4 + 6), and (4 + 8). Among them, (2 + 4 + 6) contains the maximum number of integers. Note that finalSum cannot be split into (2 + 2 + 4 + 4) as all the numbers should be unique.

Return a list of integers that represent a valid split containing a maximum number of integers. If no valid split exists for finalSum, return an empty list. You may return the integers in any order.

Example 1:

Input: finalSum = 12
Output: [2,4,6]
Explanation: The following are valid splits: (12), (2 + 10), (2 + 4 + 6), and (4 + 8).
(2 + 4 + 6) has the maximum number of integers, which is 3. Thus, we return [2,4,6].
Note that [2,6,4], [6,2,4], etc. are also accepted.

Example 2:

Input: finalSum = 7
Output: []
Explanation: There are no valid splits for the given finalSum.
Thus, we return an empty array.

Example 3:

Input: finalSum = 28
Output: [6,8,2,12]
Explanation: The following are valid splits: (2 + 26), (6 + 8 + 2 + 12), and (4 + 24). 
(6 + 8 + 2 + 12) has the maximum number of integers, which is 4. Thus, we return [6,8,2,12].
Note that [10,2,4,12], [6,2,4,16], etc. are also accepted.

Constraints:

• 1 <= finalSum <= 1010

Solution: Greedy

The get the maximum number of elements, we must use the smallest numbers.

[2, 4, 6, …, 2k, x], where x > 2k
let s = 2 + 4 + … + 2k, x = num – s
since num is odd and s is also odd, so thus x = num – s.

Time complexity: O(sqrt(num)) for constructing outputs.
Space complexity: O(1)

// Author: Huahua
class Solution {
public:
  vector<long long> maximumEvenSplit(long long finalSum) {
    if (finalSum & 1) return {};
    vector<long long> ans;
    long long s = 0;
    for (long long i = 2; s + i <= finalSum; s += i, i += 2)
      ans.push_back(i);
    ans.back() += (finalSum - s);
    return ans;
  }
};