Syllabus for |
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| TDA416 - Data structures and algorithms |
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| Syllabus adopted 2014-02-25 by Head of Programme (or corresponding) |
| Owner: TKITE |
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7,5 Credits |
| Grading: TH - Five, Four, Three, Not passed |
| Education cycle: First-cycle |
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Major subject: Information Technology
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Department: 37 - COMPUTER SCIENCE AND ENGINEERING
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Teaching language: Swedish
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Credit distribution |
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Examination dates |
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Sp1 |
Sp2 |
Sp3 |
Sp4 |
Summer course |
No Sp |
| 0105 |
Examination |
7,5 c |
Grading: TH |
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7,5 c
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14 Mar 2016 am SB, |
18 Aug 2016 am M |
| 0205 |
Laboratory |
0,0 c |
Grading: UG |
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0,0 c
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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)
Examiner:
Univ adjunkt
Erland Holmström
Replaces
TDA415
Data structures
Go to Course Homepage
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.