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TDT4120 - Algorithms and Data Structures

About

Examination arrangement

Examination arrangement: Home examination
Grade: Passed/Failed

Evaluation form Weighting Duration Examination aids Grade deviation
Home examination 100/100 4 hours

Course content

Methods for analysing the efficiency of algorithms, divide and conquer techniques, recursive solution methods. Methods for ordering, searching and sorting. Data structures for efficient retrieval of data, dynamic programming and greedy algorithms. Data structures for implementing graphs and networks, as well as methods for traversals and searches. Algorithms for finding the best path(s) and matchings, spanning trees and maximum flow. Theory of problem complexity. Algorithms are expressed in a language-independent manner.

Learning outcome

Knowledge – the candidate should have knowledge about:
- A broad spectrum of established algorithms that are useful in several areas of application.
- Classical algorithmic problems with known efficient solutions.
- Complex problems without known efficient solutions.

Skills – the candidate should be able to:
- Analyze the efficiency of an algorithm to achieve good solutions for a given problem.
- Formulate a problem so it can be handled in a rational manner by an algorithm.
- Use well-known design methods to construct new efficient algorithms.

General competence – the candidate should be able to:
- Use well-known algorithms and available program modules on new problems.
- Develop and implement new solutions for complex problems with a basis in practical reality.

Learning methods and activities

Lectures and individual exercises.

Compulsory assignments

  • Exercises

Further on evaluation

If there is a re-sit examination, the examination form may change from written to oral.

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Course materials

Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms, third edition. (This may change.)

Credit reductions

Course code Reduction From To
SIF8010 7.5
IT1105 7.5
MNFIT115 7.5
MNFIT112 7.5
IDATA2302 7.5 01.09.2020
IDATT2101 7.5
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Facts

Version: 1
Credits:  7.5 SP
Study level: Intermediate course, level II

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

No.of lecture hours: 2
Lab hours: 3
No.of specialization hours: 7

Language of instruction: Norwegian

Location: Trondheim

Subject area(s)
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science

Phone:

Examination

Examination arrangement: Home examination

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD Home examination 100/100

Release 2020-11-24

Submission 2020-11-24

Release 09:00

Submission 13:00

INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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