LeetCode每日一题(216. Combination Sum III)

给定k和n,找到1到9中不重复的k个数字,使它们的和等于n。文章通过一个例子解释了问题,并提到之前使用Golang解决过,这次用Rust实现时遇到一个小错误,通过动态规划(dp)解决,其中dp[k][d][curr]表示剩余挑选次数、与目标差值及当前数字的情况。注意curr必须递增,避免重复数字。最终返回的边界条件是k=1且d=curr,最初错误的边界条件导致了重复组合。

Find all valid combinations of k numbers that sum up to n such that the following conditions are true:

Only numbers 1 through 9 are used.
Each number is used at most once.
Return a list of all possible valid combinations. The list must not contain the same combination twice, and the combinations may be returned in any order.

Example 1:

Input: k = 3, n = 7
Output: [[1,2,4]]

Explanation:
1 + 2 + 4 = 7
There are no other valid combinations.

Example 2:

Input: k = 3, n = 9
Output: [[1,2,6],[1,3,5],[2,3,4]]

Explanation:
1 + 2 + 6 = 9
1 + 3 + 5 = 9
2 + 3 + 4 = 9
There are no other valid combinations.

Example 3:

Input: k = 4, n = 1
Output: []

Explanation: There are no valid combinations.
Using 4 different numbers in the range [1,9], the smallest sum we can get is 1+2+3+4 = 10 and since 10 > 1, there are no valid combination.

Constraints:

  • 2 <= k <= 9
  • 1 <= n <= 60

以前用 golang 实现过一次, 这次换 rust 来实现, 结果被一个小失误绊了一个多小时
用 dp 来解, dp[k][d][curr]代表还剩余 k 次挑选机会,与目标数 n 的差异为 d,当前数字为 curr 的情况下的所有组合, 要注意的是, 我们的 curr 一定得是单向递增的, 这样才不会出现挑选重复数字的情况。但是要注意的是, 最终返回边界条件是 k1 且 dcurr, 最开始我认为只要 d >= curr 且 d < 9 就可以返回, 但是这样会导致出现重复的组合。



use std::collections::HashMap;

impl Solution {
    fn dp(k: i32, n: i32, curr: i32, cache: &mut HashMap<(i32, i32, i32), Vec<Vec<i32>>>) -> Vec<Vec<i32>> {
        let mut ans = Vec::new();
        if k == 1 {
            if n == curr {
                return vec![vec![n]];
            }
            return ans;
        }
        for i in curr + 1..10 {
            let mut next = if let Some(c) = cache.get(&(k - 1, n - curr, i)) {
                c.clone()
            } else {
                Solution::dp(k - 1, n - curr, i, cache)
            };
            next.iter_mut().for_each(|l| l.push(curr));
            ans.extend(next);
        }
        cache.insert((k, n, curr), ans.clone());
        ans
    }
    pub fn combination_sum3(k: i32, n: i32) -> Vec<Vec<i32>> {
        let mut ans = Vec::new();
        let mut cache = HashMap::new();
        for i in 1..10 {
            let next = Solution::dp(k, n, i, &mut cache);
            ans.extend(next);
        }
        ans
    }
}

### LeetCode Top 100 Popular Problems LeetCode provides an extensive collection of algorithmic challenges designed to help developers prepare for technical interviews and enhance their problem-solving skills. The platform categorizes these problems based on popularity, difficulty level, and frequency asked during tech interviews. The following list represents a curated selection of the most frequently practiced 100 problems from LeetCode: #### Array & String Manipulation 1. Two Sum[^2] 2. Add Two Numbers (Linked List)[^2] 3. Longest Substring Without Repeating Characters #### Dynamic Programming 4. Climbing Stairs 5. Coin Change 6. House Robber #### Depth-First Search (DFS) / Breadth-First Search (BFS) 7. Binary Tree Level Order Traversal[^3] 8. Surrounded Regions 9. Number of Islands #### Backtracking 10. Combination Sum 11. Subsets 12. Permutations #### Greedy Algorithms 13. Jump Game 14. Gas Station 15. Task Scheduler #### Sliding Window Technique 16. Minimum Size Subarray Sum 17. Longest Repeating Character Replacement #### Bit Manipulation 18. Single Number[^1] 19. Maximum Product of Word Lengths 20. Reverse Bits This list continues up until reaching approximately 100 items covering various categories including but not limited to Trees, Graphs, Sorting, Searching, Math, Design Patterns, etc.. Each category contains multiple representative questions that cover fundamental concepts as well as advanced techniques required by leading technology companies when conducting software engineering candidate assessments. For those interested in improving logical thinking through gaming activities outside traditional study methods, certain types of video games have been shown beneficial effects similar to engaging directly within competitive coding platforms [^4]. --related questions-- 1. How does participating in online coding competitions benefit personal development? 2. What specific advantages do DFS/BFS algorithms offer compared to other traversal strategies? 3. Can you provide examples illustrating how bit manipulation improves performance efficiency? 4. In what ways might regular participation in programming contests influence job interview success rates? 5. Are there any notable differences between solving problems on paper versus implementing solutions programmatically?
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