Search course

​​​​
​​

Syllabus for

TDA416 - Data structures and algorithms

Owner: TKITE
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: First-cycle
Major subject: Information Technology
Department: 37 - COMPUTER SCIENCE AND ENGINEERING

Teaching language: Swedish

 Course module Credit distribution Examination dates Sp1 Sp2 Sp3 Sp4 Summer course No Sp 0105 Examination 7,5 c Grading: TH 7,5 c 14 Mar 2016 am SB, 18 Aug 2016 am M 0205 Laboratory 0,0 c Grading: UG 0,0 c

In programs

MPSYS SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (elective)
TKELT ELECTRICAL ENGINEERING, Year 3 (compulsory elective)
TKITE SOFTWARE ENGINEERING, Year 2 (compulsory)

Replaces

TDA415   Data structures

Eligibility:

In order to be eligible for a first cycle course the applicant needs to fulfil the general and specific entry requirements of the programme(s) that has the course included in the study programme.

Course specific prerequisites

Programming courses in basic object-oriented programming.
Basic mathematical concepts as sets, functions, relations graphs, logarithms and proof by induction.

Aim

To understand how to store and manage large amount of data effectively. Furthermore how to analyse the efficiency of different methods of storing data.

Learning outcomes (after completion of the course the student should be able to)

- understand and use basic data structures as stacks, queues, tables and graphs;
- use the algorithms connected to efficient data strucktures and understand why they are correct;
- analyze the efficiancy of the algorithms;
- make motivated choices between different data structures for different applications.

The student should also in practice be able to:
- implement abstrakt data types as Java interfaces and data structures;
- analyze the efficiency of different implementations, for exampel sorting algorithms;
- use the standard library of data structures and algorithms;

Content

Abstract datatypes, simple analysis of imperative code. Common data structures, such as arrays, lists, trees and (hash)tables, usage of these data structures to implement stacks, queues, prority queues, lexica and graphs and other abstract datatypes. Standard algorithms on these structures. Common techniques for algorithm design. Standard algorithms libraries.

Organisation

Lectures, exercise classes, and laborations.

Literature

See course homepage.

Examination

Laborations and written exam.

Page manager Published: Thu 04 Feb 2021.