2026/27 · 官方课程目录版本
该 PDF 文件注明的生效学期为 Semester A 2025/26。
这版课程介绍仍在逐项核对。选课前，请对照下方校方原文件确认修读条件和考核要求。
2026/27 开课安排尚未核对。选课前请在 AIMS 确认可选课节。
The PDF Effective Term is separate from the 2026/27 catalogue year and current offering observation.
这门课学什么
港真课程概览
从程序正确性和复杂度分析出发，讨论排序、选择算法及常见抽象资料型态，并延伸至平衡树、散列和图结构。
- 课程简介
- This course aims to provide students an appreciation to the fundamentals of computer science. Models and applications of data structures including heaps, search trees, hash tables and disjoint sets are introduced and evaluated. Mathematical tools for analysis of algorithms and data structures are discussed and applied. Students are given the opportunity to develop and implement applications of the data structures and their derivatives.
校方 PDF 第 2 页 · Abstract
- 课程内容
- Program correctness. Complexities of programs: notation, average and worst case analysis, complexities of common programming constructs. Sorting algorithms: merge sort, heap sort, quicksort, bucket sort. Algorithms for order statistics. Abstract data types: stacks, queues, heaps. Balanced search trees: AVL trees, red-black trees, B-trees. Game Trees. Hash tables. Disjoint sets. Graphs. Syllabus: • Program correctness and complexities Techniques for proving program correctness, e.g., loop invariant and induction. Asymptotic notations for program complexities. Summation and recurrence formulas. Complexities of common programming constructs, e.g., loops and recursive programs. Average and worst case analysis. • Sorting algorithms Selected sorting algorithms, such as merge sort, heap sort, quicksort, bucket sort, radix sort, as examples to illustrate the previous concepts and analysis techniques. Algorithms for order statistics. • Review of abstract data types Principles of abstract data types. Examples: stacks, queues, heaps. • Search trees Binary search trees. Balanced search trees: AVL trees, splay trees, red-black trees, B-trees. • Game trees Minimax Rules. Alpha-Beta Pruning. Reducing searching depth. • Hash tables Hash functions. Collision resolution. Rehashing • Disjoint Set Disjoint set operations. Path compression. Ackermann’s function. • Graphs Adjacency Matrix, Depth First Search, Breadth First Search • Selected advanced topics in Data Structures
校方 PDF 第 5 页 · Keyword Syllabus
- 预期学习成果
查看校方学习成果与对应条件
CILOs Weighting (if DEC-A1 DEC-A2 DEC-A3 app.) 1 Implement common data structures and x algorithms. 2 Analyse efficiency and correctness of algorithms x using mathematical techniques. 3 Evaluate and compare similar data structures x x and algorithms. 4 Design and apply appropriate data structures to x x solve problems.校方 PDF 第 2 页 · Course Intended Learning Outcomes (CILOs)
我能不能修这门课
先修、建议先备和并修要求分别查看；等同及互斥条件也会影响选课。and 表示同时满足，or 表示备选；组合条件按下方原文分组阅读。
- 先修条件
- CS2310 Computer Programming or CS2311 Computer Programming or CS2312 Problem Solving and Programming or equivalent
校方 PDF 第 1 页 · Prerequisites
- 建议先备知识
- 无（校方注明 Nil）
校方 PDF 第 1 页 · Precursors
- 并修要求
- 该版官方课纲未列明该项。
- 其他修读要求
- 该版官方课纲未列明该项。
- 等同课程及条件
- 无（校方注明 Nil）
校方 PDF 第 1 页 · Equivalent Courses
- 互斥课程及条件
- CS2334 Data Structures for Data Science
校方 PDF 第 1 页 · Exclusive Courses
怎么考，怎样才算通过
- 考核方式
- Continuous Assessment (%): 40; Examination (%): 60; Examination Duration (Hours): 2
查看校方原始考核表与使用要求
ATs CILO No. Weighting (%) Remarks ("-" for Allow Use of nil entry) GenAI? 1 Assignments 1, 2, 3, 4 25 Students are Yes required to work on assignments at least once every four weeks. 1. Students may use GenAI tools to assist with understanding concepts or generating ideas, but all submissions must reflect their own understanding and effort. Directly copying and pasting answers generated by GenAI into assignments is strictly prohibited. 2. Uploading entire assignment questions, datasets, or other course materials directly to GenAI tools to obtain answers is not allowed. 3. If significant assistance is obtained from GenAI tools, students must clearly document the nature and scope of its use in their submissions. 2 Quiz 1, 2, 3, 4 15 - No校方 PDF 第 3 页 · Continuous Assessment (%),Examination (%),Examination Duration (Hours)
- 通过条件
- Minimum Examination Passing Requirement (%): 30 Additional Information for ATs: For a student to pass the course, at least 40% of the maximum mark for the continuous assessment and 30% of the maximum mark for the examination must be obtained.
校方 PDF 第 4 页 · Minimum Examination Passing Requirement (%),Additional Information for ATs
学分、时长与版本信息
- 本版本课程名称
- Data Structures
校方 PDF 第 1 页 · Course Title
- 本版本学分
- 3
校方 PDF 第 1 页 · Credit Units
- 修读时长
- One Semester
校方 PDF 第 1 页 · Course Duration
- 课纲生效学期
- Semester A 2025/26
- 课纲列明的级别
- B1, B2, B3, B4 - Bachelor's Degree
校方 PDF 第 1 页 · Level
核对官方原文件
可通过下方校方链接阅读或下载该版原始 PDF。 CS3334 · 打开校方原始 PDF ↗
来源 · 校方课程介绍 ↗ · 查阅 2026-10-20T13:27:19.552Z