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| 1.
| [Mathematics foundation]
understand the concept of time, space complexity and analyze the time and space complexities of an algorithm and a data structure. |
| 2.
| [Data structures]
understand well-known generic data structures such as stack, queue, tree and related algorithms and apply them to solve problems. |
| 3.
| [Problem solving]
design new data structures and algorithms to solve problems. |
| 4.
| [Implementation]
implement selected data structures and algorithms. |
Mapping from Course Learning Outcomes to Programme Learning Outcomes
| | PLO a | PLO b | PLO c | PLO d | PLO e | PLO f | PLO g | PLO h | PLO i | PLO j |
| CLO 1 | T,P | | | | | | | | | |
| CLO 2 | | T,P | | | | | | | | |
| CLO 3 | | | T,P | | | | | | | |
| CLO 4 | | | | T,P | | | | | | |
T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to
here.
|
| Syllabus |
|
Calendar Entry:
Arrays, linked lists, trees and graphs; stacks and queues; symbol tables; priority queues, balanced trees; sorting algorithms; complexity analysis.
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|
Detailed Description:
| Mathematics foundation |
Mapped to CLOs
|
| Growth of functions, recurrences, time and space complexity | 1 |
| Basic data structures and algorithms |
Mapped to CLOs
|
| Array, linked list, stack, queue, trees, hashing, graphs, sorting and searching algorithms | 2, 3, 4 |
| Advanced data structures and algorithms |
Mapped to CLOs
|
| Balanced tree, heap, priority queue, sorting in linear time | 2, 3, 4 |
| Lower bound |
Mapped to CLOs
|
| Techniques for proving lower bounds, lower bound for sorting | 1 |
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|
Assessment:
Continuous Assessment:
40%
Written Examination:
60%
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| Teaching Plan |
|
Please refer to the corresponding Moodle course.
|
| Moodle Course(s) |
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