Coding Interview Resources
前往频道在 Telegram
This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data
显示更多📈 Telegram 频道 Coding Interview Resources 的分析概览
频道 Coding Interview Resources (@crackingthecodinginterview) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 52 119 名订阅者,在 技术与应用 类别中位列第 2 568,并在 印度 地区排名第 7 219 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 52 119 名订阅者。
根据 07 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 156,过去 24 小时变化为 4,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 2.10%。内容发布后 24 小时内通常能获得 0.82% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 094 次浏览,首日通常累积 425 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 2。
- 主题关注点: 内容集中在 array, stack, algorithm, programming, sort 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“This channel contains the free resources and solution of coding problems which are usually asked in the interviews.
Managed by: @love_data”
凭借高频更新(最新数据采集于 08 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
52 119
订阅者
+424 小时
+397 天
+15630 天
帖子存档
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Important Sorting Algorithms-
Bubble Sort: Bubble Sort is the most basic sorting algorithm, and it works by repeatedly swapping adjacent elements if they are out of order.
Merge Sort: Merge sort is a sorting technique that uses the divide and conquer strategy.
Quicksort: Quicksort is a popular sorting algorithm that performs n log n comparisons on average when sorting an array of n elements. It is a more efficient and faster sorting algorithm.
Heap Sort: Heap sort works by visualizing the array elements as a special type of complete binary tree known as a heap.
Important Searching Algorithms-
Binary Search: Binary search employs the divide and conquer strategy, in which a sorted list is divided into two halves and the item is compared to the list’s middle element. If a match is found, the middle element’s location is returned.
Breadth-First Search(BFS): Breadth-first search is a graph traversal algorithm that begins at the root node and explores all neighboring nodes.
Depth-First Search(DFS): The depth-first search (DFS) algorithm begins with the first node of the graph and proceeds to go deeper and deeper until we find the goal node or node with no children.
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