# Leetcode ## 1.Performance ### [上界與下界](https://jenhsuan.gitbook.io/algorithm/notes-of-algorithms/asymptotic-notation) * Big-Theta (Θ): asymptotic **tight** bound * Θ(g(n)) = { 存在有positive constant c1, c2, n0, 使f(n) 滿足0 ≤ c1g(n) ≤ f(n) ≤ c2g(n), n >= n0} * Big-O (O): asymptotic **upper** bound * O(g(n)) = { 存在有positive constant c, n0, 使f(n) 滿足0 ≤ f(n) ≤ cg(n), n >= n0} * Big-Omega (Ω): asymptotic **lower** bound * Ω(g(n)) = { 存在有positive constant c, n0, 使f(n) 滿足0 ≤ cg(n) ≤ f(n), n >= n0} ### 效能項目集 * 常數 constant: O(1) * 對數 logarithmic: O(log n) > e.g., 猜測演算法 (guess), 二分法 (bisection) * 次線性 sublinear: O(n ^ d), d < 1 > e.g., k-d tree * 線性 linear: O(n) > e.g.,addition * 線性對數 linearithmic: O(n log n) > e.g., divide and conquer * 二次方 quadratic: O(n^2) * 指數 exponential: O(2^n) ## 2.Algorithm ### \[1.分治法 Divide and Conquer] > 分為解析 (真正處理問題的程序)以及以及遞迴, 如果解析需要O(n)時間, 則每次都分為兩半則總共需要O(n log n)時間 ### \[2.動態規劃法 Dynamic programming] * [198.House Robber (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/198.-house-robber-easy) * [213.House Robber II (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/213.-house-robber-ii-medium) * [337.House Robber III (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/337.-house-robber-iii-medium) * [174.Dungeon Game (Hard)](https://jenhsuan.gitbook.io/algorithm/leetcode/174.-dungeon-game-hard) ## 3.Data Structure ### \[Overview] | Data structure | Access | Search | Insertion | Deletion | Properties | | ------------------------------------------------------------------------------------------------------- | ---------------- | ------------------------- | ------------------------- | ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [Binary heap](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/binary-heap) | O(1) | O(log n) | O(log n) | O(log n) |

A:直接索引

S: log n層

I:插到最後, sift up

D:移除root, 將最大值移到root後sift down root

| | Hash table | NA |

O(1) \~

O(n)

|

O(1) \~

O(n)

|

O(1) \~

O(n)

|

A:無法索引
S: 必須用Key索引
I: 計算hash值後插入
D:計算hash值後移除

W: collision

| | [Stack](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/stack) | O(n) | O(n) | O(1) | O(1) |

A:必須循覽整個序列
S:必須循覽整個序列
I:push到最上方
D:pop最上方元素

| | [Queue](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/queue) | O(n) | O(n) | O(1) | O(1) |

A:必須循覽整個序列
S:必須循覽整個序列

I:從後方enque
D:dequeue最前方元素

| | [Single linked list](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/linked-list) | O(n) | O(n) | O(1) | O(1) |

A:必須循覽整個序列

S:必須循覽整個序列

| | [Doubly linked list](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/doubly-linked-list) | O(n) | O(n) | O(1) | O(1) |

A:必須循覽整個序列

S:必須循覽整個序列

| | [Array](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/pointer-and-array) | O(1) | O(n) | O(n) | O(n) |

A:直接索引
S, I, D:必須循覽整個序列

| | Binary Search Tree | O(log n) \~ O(n) | O(log n) \~ O(n) | O(log n) \~ O(n) | O(log n) \~ O(n) |

必須循覽整個序列

W: unbalance

| | Balance Binary Search Tree | O(log n) | O(log n) | O(log n) | O(log n) | 必須循覽整個序列 | | AVL Tree | O(log n) | O(log n) | O(log n) | O(log n) | 必須循覽整個序列 | | B-Tree | O(log n) | O(log n) | O(log n) | O(log n) | 必須循覽整個序列 | | red-black tree | O(log n) | O(log n) | O(log n) | O(log n) | 必須循覽整個序列 | ### ### [\[1.Binary tree\]](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/meet-binary-tree-a-hierarchical-data-structure) > construct tree, mirror, path sum基本上都可以用recursion的方式完成, 至於是用VLR還是LRV則要看需求是由上到下, 還是由下到上 #### [Level order traversal](https://jenhsuan.gitbook.io/algorithm/notes-of-algorithms/binary-tree-traversal) * [104.Maximum Depth of Binary Tree (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/104.-maximum-depth-of-binary-tree-easy) * [102. Binary Tree Level Order Traversal (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/102.-binary-tree-level-order-traversal-medium) * [107.Binary Tree Level Order Traversal II (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/107.-binary-tree-level-order-traversal-ii-easy) * [103. Binary Tree Zigzag Level Order Traversal (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/103.-binary-tree-zigzag-level-order-traversal) #### [In-oder traversal](https://jenhsuan.gitbook.io/algorithm/notes-of-algorithms/binary-tree-traversal) * [94.Binary Tree Inorder Traversal (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/94.-binary-tree-inorder-traversal) * [98.Validate Binary Search Tree (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/98.-validate-binary-search-tree-medium) * [199.Binary Tree Right Side View (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/199.-binary-tree-right-side-view-medium) #### [Post-order traversal](https://jenhsuan.gitbook.io/algorithm/notes-of-algorithms/binary-tree-traversal) * [110.Balanced Binary Tree (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/110.-balanced-binary-tree-easy) * [145.Binary Tree Postorder Traversal (Hard)](https://jenhsuan.gitbook.io/algorithm/leetcode/145.-binary-tree-postorder-traversal-hard) #### [Pre-order traversal](https://jenhsuan.gitbook.io/algorithm/notes-of-algorithms/binary-tree-traversal) * [144.Binary Tree Preorder Traversal (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/144.-binary-tree-preorder-traversal-medium) #### Construct tree * [654.Maximum Binary Tree](https://jenhsuan.gitbook.io/algorithm/leetcode/654.-maximum-binary-tree) #### Mirror a binary tree * [226. Invert Binary Tree](https://jenhsuan.gitbook.io/algorithm/leetcode/226.-invert-binary-tree) #### Path sum * [112. Path Sum ](https://jenhsuan.gitbook.io/algorithm/leetcode/untitled) * [113. Path Sum II](https://jenhsuan.gitbook.io/algorithm/leetcode/113.-path-sum-ii) #### Lowest Common Ancestor * [235. Lowest Common Ancestor of a Binary Search Tree](https://jenhsuan.gitbook.io/algorithm/leetcode/236.-lowest-common-ancestor-of-a-binary-tree) ### \[2.Hash table] > 通過鍵值映射到表中一個位置來訪問記錄以加快查找的速度, 此映射函數就是Hash function, 存放紀錄的數組稱為Hash table * [3. Longest Substring Without Repeating Characters ](https://jenhsuan.gitbook.io/algorithm/leetcode/3.-longest-substring-without-repeating-characters) * [242. Valid Anagram](https://jenhsuan.gitbook.io/algorithm/leetcode/242.-valid-anagram) * [160. Intersection of Two Linked Lists](https://jenhsuan.gitbook.io/algorithm/leetcode/160.-intersection-of-two-linked-lists) ### [\[3.Stack\]](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/stack) > 後進先出, 有序容器 * [155. Min Stack](https://jenhsuan.gitbook.io/algorithm/leetcode/155.-min-stack-1) * 173\. Binary Search Tree Iterator ### [\[4.Queue\]](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/queue) > 先進先出, 有序容器 * [232. Implement Queue using Stacks](https://jenhsuan.gitbook.io/algorithm/leetcode/232.-implement-queue-using-stacks) ### [\[5.Linked list\]](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/linked-list) #### [Inserting node](https://jenhsuan.gitbook.io/algorithm/notes-of-algorithms/linked-list) * [147.Insertion Sort List (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/147.-insertion-sort-list-medium) #### Traversal * [234.Palindrome Linked List (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/234.-palindrome-linked-list-easy) #### Split the list * [148.Sort List (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/148.-sort-list-medium) #### Delete the node * [19.Remove Nth Node From End of List (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/19.-remove-nth-node-from-end-of-list-medium) * [203.Remove Linked List Elements](https://jenhsuan.gitbook.io/algorithm/leetcode/203.-remove-linked-list-elements) #### Reverse list * [ 206. Reverse Linked List](https://jenhsuan.gitbook.io/algorithm/leetcode/206.-reverse-linked-list) #### Others * [23.Merge k Sorted Lists (Hard)](https://jenhsuan.gitbook.io/algorithm/leetcode/23.-merge-k-sorted-lists-hard) * [2. Add Two Numbers](https://jenhsuan.gitbook.io/algorithm/leetcode/2.-add-two-numbers) * **21. Merge Two Sorted Lists** ### ### \[6.Array] * 349\. Intersection of Two Arrays * 442.Find All Duplicates in an Array * 189\. Rotate Array ### ### \[7.Point] #### 取址 * 449\. Serialize and Deserialize BST ### ### \[8.Binary search tree] * [98.Validate Binary Search Tree (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/98.-validate-binary-search-tree-medium) #### Minimum * [230. Kth Smallest Element in a BST](https://jenhsuan.gitbook.io/algorithm/leetcode/230.-kth-smallest-element-in-a-bst) #### Balance tree * [110.Balanced Binary Tree (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/110.-balanced-binary-tree-easy) * 109\. Convert Sorted List to Binary Search Tree #### Find unique BST * [96. Unique Binary Search Trees](https://jenhsuan.gitbook.io/algorithm/leetcode/96.-unique-binary-search-trees) * 95\. Unique Binary Search Trees II #### Search * [700. Search in a Binary Search Tree](https://jenhsuan.gitbook.io/algorithm/leetcode/700.-search-in-a-binary-search-tree) #### Insert node * [701. Insert into a Binary Search Tree](https://jenhsuan.gitbook.io/algorithm/leetcode/701.-insert-into-a-binary-search-tree) #### Remove node * 450\. Delete Node in a BST #### Traversal * 653\. Two Sum IV - Input is a BST * 449\. Serialize and Deserialize BST * 783\. Minimum Distance Between BST Nodes #### Iterator * 173\. Binary Search Tree Iterator ## 4.Sorting ### \[Overview] * 最佳, 最糟, 平均 (難以量化): 時間複雜度, 額外空間, 穩定性 | Algorithm | Best | Average | Worst | Space | Stability | Type | Properties | | ----------------------------------------------------------------------------------------------- | ---------- | ---------- | ---------- | ---------------- | --------- | -------- | ------------------------------------------------------------------ | | [Insertion sort](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/insertion-sort) | O(n) | O(n^2) | O(n^2) | O(1) | 穩定 | 換位排序 |

1.最佳情形比quick還快(少量元素未排序時)

2.w出現於元素隨機出現時

| | [Selection sort](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/selection-sort) | O(n^2) | O(n^2) | O(n^2) | O(1) | 不穩定 | 換位排序 | 所有排序法最慢的一種, 不會用到前面的結果 | | [Heap sort](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/heap-sort) | O(n log n) | O(n log n) | O(n log n) | O(1) | 不穩定 | 換位排序 | 最糟/最佳都是O(n log n) | | [Quick sort](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/quick-sort) | O(n log n) | O(n log n) | O(n^2) | O(log n) \~ O(n) | 穩定 | 分割排序 |

1最糟情形出現在分為"空"與"大"兩個集合時

2.平均情形比Heap sort快誒, 通常會勝過其他演算法

| | Bucket sort | O(n) | O(n) | O(n) | O(n \* k) | 穩定 | 非比較排序 | | | Counting sort | O(n + k) | O(n + k) | O(n + k) | O(n + k) | 穩定 | 非比較排序 | | | [Merge sort](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/merge-sort) | O(n log n) | O(n log n) | O(n log n) | O(n) | 穩定 | 需要額外空間排序 | 運用外部資料進行資料轉換最簡單的一個 | ### \[1.換位排序 (Transposition sorting)] > 與其他元素進行換位將他們移動到正確的位置 #### [1.插入排序 (Insertion sort)](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/insertion-sort) > 簡述:\ > 從最左開始往右滑動, 左邊已滑動過的位置必須是一個sorted list\ > \ > 使用時機/特性: \ > 只有少數項目或是大部分項目已排序時適用, 一旦當前的元素比sorted list的最右邊大, 則不在繼續往下比, 移動罩窗 * [147.Insertion Sort List (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/147.-insertion-sort-list-medium) * [283.Move Zeroes](https://jenhsuan.gitbook.io/algorithm/leetcode/283.-move-zeroes) * [56.Merge Intervals](https://jenhsuan.gitbook.io/algorithm/leetcode/56.-merge-intervals) #### [2.選擇排序 (Selection sort)](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/selection-sort) > 簡述:\ > 從最左開始往右滑動, 將元素跟左邊剩下的元素逐一比較並找出最小值位置後swap\ > \ > 使用時機/特性:\ > 所有排序法最慢的, 每個重複過程沒有利用上一次的結果來做效能的提升 #### [3.堆積排序 (Heap sort)](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/heap-sort) > 簡述:\ > 將list轉換成堆積(heap), 迭代呼叫headify處理 \ > \ > 使用時機/特性:\ > 在意最糟情形的發生 ### \[2.分割排序 (Partition-Based sorting)] > 分治法是將問題拆成兩個獨立的子問題來解決, 每個子問題大約是原問題的一半, 關鍵點是如何挑選set的中位數 (pivot) #### [1.快速排序 (Quick sort)](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/quick-sort) > 描述:\ > 1.Partition: 一開始的pivot為最左邊元素, 將l , h交換後, 將h, pivot互換, 返回h\ > 2.QuickSort: 呼叫partition, 以及pivot index剖半後的兩個陣列, 再次呼叫Quicksort\ > \ > 使用時機/特性: \ > 只對大型陣列使用快速排序, 對小型陣列使用插入排序 * [215.Kth Largest Element in an Array (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/215.-kth-largest-element-in-an-array-medium) ### \[3.非比較動作的排序] > 非比較排序就沒有效能上的限制, 通常可在O(n)完成但缺少靈活性; 比較排序較常應用於實際工作上, 如Mozilla的sort是實作merge sort, webkit是實作selection sort #### 1.桶子排序 (Bucket sort) > 簡述\ > 桶子是有序容器, 計算所需要桶子的數量後, 將相同區間的成員塞入(排序), 再依序將桶子內的成員倒出即完成\ > 使用時機: \ > 1.均勻分布: 輸入資料必須均勻分布於特定範圍, 依據這個分布建立n個桶子均勻分割此輸入範圍\ > 2.有序的雜湊函數: 桶子是有序的. 如果 i < j, 插入桶子bi的元素依字典序會小於桶子bj元素\ > 不適用的場合:\ > 不適合排序任意的字串, 因為不可能開發一個具有需求字元的雜湊函式 * [347.Top K Frequent Elements](https://jenhsuan.gitbook.io/algorithm/leetcode/347.-top-k-frequent-elements) * [164. Maximum Gap](https://jenhsuan.gitbook.io/algorithm/leetcode/164.-maximum-gap) #### 2.計數排序 (Counting sort) > 最佳, 最差: 複雜度O(n + k), 當k沒有很大時近似於線性\ > 使用時機: 對輸入序列為不超過k, 長度為k 的整數序列可使用\ > 屬於穩定排序法 * [75.Sort Colors (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/75.-sort-colors-medium) ### \[4.用額外的儲存空間排序] > 大部分的排序演算法不需要任何明顯的額外儲存空間 #### [1. 合併排序 (Merge sort)](https://jenhsuan.gitbook.io/algorithm/algorithms-in-a-nutshell/merge-sort) > 最佳, 最差: 複雜度O(n log n)\ > 空間複雜度: 需要額外的O(n) * [23.Merge k So rted Lists (Hard)](https://jenhsuan.gitbook.io/algorithm/leetcode/23.-merge-k-sorted-lists-hard) * [4.Median of Two Sorted Arrays](https://jenhsuan.gitbook.io/algorithm/leetcode/4.-median-of-two-sorted-arrays) * 95\. Unique Binary Search Trees II ### \[5.其他] #### 1.Binary sort * [148.Sort List (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/148.-sort-list-medium) ## 5.Search ### \[Overview] | Algorithm | Best | Average | Worst | Property | | -------------------------- | ---------------- | ---------------- | ---------------- | --------------------------------------------------------------------------------------------------------------------------------- | | Sequential search | O(1) | O(n) | O(n) | | | Binary search | O(1) | O(n log n) | O(log n) | | | Hash search | O(1) | O(1) | O(n) |

W: If too many elements
were hashed into the same key:
looking inside this key may take O(n) time

| | Binary Search Tree | O(log n) \~ O(n) | O(log n) \~ O(n) | O(log n) \~ O(n) | **W:** completely unbalance tree | | Balance Binary Search Tree | O(log n) | O(log n) | O(log n) | | | AVL tree | O(log n) | O(log n) | O(log n) | | | B-Tree | O(log n) | O(log n) | O(log n) | | | red-black Tree | O(log n) | O(log n) | O(log n) | | ### \[1.Binary search] > 對已排序的合集排序, 切對半直到確定此項目不出現在合集中 * [33. Search in Rotated Sorted Array](https://jenhsuan.gitbook.io/algorithm/leetcode/33.-search-in-rotated-sorted-array) [(Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/147.-insertion-sort-list-medium) * [35.Search Insert Position (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/35.-search-insert-position-easy) ### ### \[2.Hash search] > 預先處理 : 計算Ci的雜湊值, hi = hash(Ci), 再將值放入: H\[hi] -> O(n)\ > 關注點: 雜湊函數的設計以及碰撞的處理\ > 搜尋的步驟: \ > 1.計算雜湊值: 運算成本必定在**固定常數**的上界\ > 2.存取由雜湊值索引的雜湊表項目: **固定常數**的上界\ > 3.在碰撞的存在中找尋特定項目 ### ### \[3.Binary search tree] > 當合集內容變動頻繁時:\ > **二元搜尋**的缺點: 使用已排序陣列會大幅降低演算法的效能\ > **雜湊搜尋**的缺點: 由於不會預先知道要儲存的元素個數, 所以選擇適當大小的雜湊表不是容易的事情\ > 使用時機:\ > 1.必須以遞減/遞增順序走訪資料\ > 2.資料合集的大小未知, 而且實做必須能夠處理放入記憶體中任何可能的大小內容\ > 3.資料合集呈現高度動態, -而且合集的生命週期間有許多插入和刪除動作 ### \[4.Balance Binary Search Tree] > 對平衡的樹而言, 在while迴圈的每次重複過程中, 要搜尋的合集大小會減少一半, 因此有O(log n)的效能 #### AVL Tree > 1.樹葉節點的高度為0, 非樹葉節點的高度為1, 不存在的子節點的高度為-1\ > 2.任意節點的高度差異為-1, 0, 1\ > 3.每個節點會儲存自己的高度值 ## 6.Graph ### \[Overview] | Algorithm | Best | Average | Worst | Property | | -------------------- | -------- | -------- | -------- | -------- | | Breadth-First Search | O(V + E) | O(V + E) | O(V + E) | | | Depth-First Search | O(V + E) | O(V + E) | O(V + E) | | ### \[1.Breadth-First Search] > 保證找出最短路徑 * [127.Word Ladder (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/127.-word-ladder-medium) * [104.Maximum Depth of Binary Tree (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/104.-maximum-depth-of-binary-tree-easy) * [102. Binary Tree Level Order Traversal (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/102.-binary-tree-level-order-traversal-medium) * [107.Binary Tree Level Order Traversal II (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/107.-binary-tree-level-order-traversal-ii-easy) * [103. Binary Tree Zigzag Level Order Traversal (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/103.-binary-tree-zigzag-level-order-traversal)
### \[2.Depth-First Search] > 會盡可能找出較多的路徑, 但不一定是最短路徑 * [337.House Robber III (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/337.-house-robber-iii-medium) * [130.Surrounded Regions (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/130.-surrounded-regions-medium) ## 7.General problem ### \[1.Palindrome] * [9. Palindrome Number (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/9.-palindrome-number-easy) * [409.Longest Palindrome (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/409.-longest-palindrome-easy) * [234.Palindrome Linked List (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/234.-palindrome-linked-list-easy) * **5. Longest Palindromic Substring** ### \[2.Zigzag] * [6.ZigZag Conversion (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/6.zigzag-conversion-medium) ### \[3.Recursion] #### Back tracking * [78.Subsets](https://jenhsuan.gitbook.io/algorithm/leetcode/78.-subsets) * [46.Permutations (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/46.-permutations-medium) * [47.Permutations II (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/47.-permutations-ii-medium) * [654.Maximum Binary Tree](https://jenhsuan.gitbook.io/algorithm/leetcode/654.-maximum-binary-tree) * 95\. Unique Binary Search Trees II * 17\. Letter Combinations of a Phone Number * **22. Generate Parentheses** ### \[4.Others] * [283.Move Zeroes](https://jenhsuan.gitbook.io/algorithm/leetcode/283.-move-zeroes) * [73.Set Matrix Zeroes (Medium)](https://jenhsuan.gitbook.io/algorithm/leetcode/73.-set-matrix-zeroes-medium) * [169.Majority Element (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/169.-majority-element-easy) * [1.Two Sum (Easy)](https://jenhsuan.gitbook.io/algorithm/leetcode/1.-two-sum) * [15. 3Sum](https://jenhsuan.gitbook.io/algorithm/leetcode/15.-3sum) * 7\. Reverse Integer * 8\. String to Integer (atoi) * 11\. Container With Most Water * 13\. Roman to Integer * **12. Integer to Roman** * **14. Longest Common Prefix** ### --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://jenhsuan.gitbook.io/algorithm/leetcode.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.