2022/23 Undergraduate Module Catalogue
XJCO2711 Algorithms and Data Structures I
10 creditsClass Size: 100
Module manager: Dr Natasha Shakhlevich
Email: N.Shakhlevich@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2022/23
This module is not approved as a discovery module
Module summary
Algorithms are the underlying concept of which computer programs are the embodiment of. In order to appreciate a good solution to a problem it is essential that 'good' can be quantified in some rigorous manner. The primary focus of this module is to develop a tool-kit of knowledge and skills used in the design and analysis of algorithms and data structures.This module builds on previous mathematics modules and relies on the skills developed there for justifying the correctness of algorithms and their time and space requirements.Objectives
This module introduces the basics of algorithm design and analysis and provides students with the opportunity to practice these new skills on classical computer science algorithms and data structures. This module develops abstract problem solving skills and contributes to developing computer science professional who are capable of tackling real world problems.Learning outcomes
On successful completion of this module a student will have demonstrated the ability to:
- analyse an algorithm in terms of time complexity.
- justify the correctness of an algorithm.
- trace an algorithm communicated in pseudo code.
- develop algorithms for real world problems.
- select an appropriate data structures for a given problem.
- articulate key concepts from the topic in a clear and rigorous manner.
Syllabus
Syllabus This module covers the following 4 topic areas:
-Algorithm design : iterative algorithms, recursive algorithms, brute force algorithms and divide-and-conquer.
-Algorithm analysis : time and space complexity, worst case analysis and big-O notation.
-Searching & Sorting : sequential and binary search, selection sort, insertion sort, quicksort, mergesort and heapsort.
-Data structures : arrays, lists, stacks, queues and heaps.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 20 | 1.00 | 20.00 |
| Tutorial | 10 | 1.00 | 10.00 |
| Private study hours | 70.00 | ||
| Total Contact hours | 30.00 | ||
| Total hours (100hr per 10 credits) | 100.00 | ||
Private study
Taught session preparation: 9 hoursTaught session follow-up: 9 hours
Self-directed study: 19 hours
Assessment activities: 24 hours
This module is re-assessed by exam only.
Opportunities for Formative Feedback
Coursework and labs.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| In-course Assessment | Coursework 1 | 10.00 |
| In-course Assessment | Coursework 2 | 10.00 |
| Total percentage (Assessment Coursework) | 20.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
| Exam type | Exam duration | % of formal assessment |
| Standard exam (closed essays, MCQs etc) | 2 hr 00 mins | 80.00 |
| Total percentage (Assessment Exams) | 80.00 | |
This module will be reassessed by an online time-limited assessment.
Reading list
The reading list is available from the Library websiteLast updated: 01/06/2022 16:59:02
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