Algorithms And Data Structures (M) COMPSCI5004

  • Academic Session: 2023-24
  • School: School of Computing Science
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No

Short Description

To study the concept of algorithms, and how to analyse their efficiency; To study the concept of abstract data types, and the abstract data types most commonly used in software development; To study the basic data structures most commonly used to represent these abstract data types, together with algorithms operating on these data structures.

Timetable

TBC

Requirements of Entry

COMPSCI4039  Programming (H)

(or equivalent)

Excluded Courses

None 

Co-requisites

None

Assessment

Exam 80%, assignments 20%.

Main Assessment In: April/May

Are reassessment opportunities available for all summative assessments? No

The coursework cannot be redone because the feedback provided to the students after the original coursework would give any students redoing the coursework an unfair advantage.

 

Students can resit the class test

Course Aims

To study the concept of algorithms, and how to analyse their efficiency; To study the concept of abstract data types, and the abstract data types most commonly used in software development; To study the basic data structures most commonly used to represent these abstract data types, together with algorithms operating on these data structures.

Intended Learning Outcomes of Course

By the end of the course students will be able to:

1: Discuss the concepts of algorithms and algorithm complexity;

2: Use an abstract data type (ADT);

3: Identify commonly used to represent the above ADTs (arrays, linked lists, search trees, hash tables);

4: Describe algorithms expressed in a suitable notation;

5: Use basic insertion, deletion, searching, merging, and sorting algorithms;

6: Implement these algorithms in a suitable programming language;

7: Detail complexity of these algorithms;

8: Use recursion in algorithms and programs;

9: Describe ADTs specified informally;

10: Design, specify, and implement ADTs;

11: Code standard ADTs (strings, stacks, queues, lists, sets, maps, trees, graphs);

12: Recognise how to decide which ADTs are suitable for use in particular programs;

13: Implement these data structures in a suitable programming language;

14: Describe how the complexity of ADT operations is affected by the choice of data structures.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.