Computer Engineering BA (B), Data Structures and Algorithms, 7.5 credits

Aim

This course aims to familiarize students with relevant theoretical concepts and practical implementation regarding creating, storing, retrieving, ordering, and manipulation of data structures, abstract data types (ADTs), and the basics of analysis of algorithms. This course also aims to form a critical approach to basic and essential topics in data structures, including lists, linked lists, hash tables, binary trees, self-balancing trees, heaps, and graphs.

Course objectives

Upon completion of this course, students should be able to:
- Analyze and compare the efficiency and complexity of different algorithms.
- Understand the properties of Abstract Data Types and implement various data structures.
- Understand and implement the associated operations of data structures.
- Understand the capabilities and limitations of different data structures and apply appropriate data structures for solving problems.
- Consider complexity issues when designing and implementing an algorithm.

Content

- Introduction to the theory of complexity (time / space comlexities) and requirements analysis for data structures and associated algorithms using Asymptotic notations. Identifying Best / Average / Worst case scenarios.
- Introduction to basic abstract data types (ADT) such as Stacks ADT, Queues ADT and List ADT and their associated algorithms.
- Introduction to recursive algorithms and divide-and-conquer approaches.
- Introduction to basic sorting algorithms.
- Introduction and implementation of complex data structures such as Stacks, queues, lists, Trees, heaps, hashing, graphs.
- Determination of a suitable data structures for a particular problem.

Entry requirements

Computer Engineering BA (A), 22.5 credits, including 15 credits in object oriented programming.

Selection rules and procedures

The selection process is in accordance with the Higher Education Ordinance and the local order of admission.

Teaching form

The teaching consists of about 17% lectures, and 6% laboratory exercises, 77% of the time is reserved for self-studying by reading the literature, preparing for the laboratory work, assignments and preparation for the exam. This can be changed if the access to the resources is different.

Examination form

L101: Labs, 3.5 Credits
Grade scale: Fail (U) or Pass (G)

Q101: Online Examination, 4 Credits
Grade scale: Seven-grade scale, A, B, C, D, E, Fx and F. Fx and F represent fail levels.

Grading criteria for the subject can be found at www.miun.se/gradingcriteria.

The examiner has the right to offer alternative examination arrangements to students who have been granted the right to special support by Mid Sweden University’s disabilities adviser.

Grading system

Seven-grade scale, A, B, C, D, E, Fx and F. Fx and F represent fail levels.

Other information

This course cannot be part of the same degree as course DT046G or DT064G.