Data Structures and Algorithms, 2 credits

Datastrukturer och algoritmer, 2 hp

TDDD71

The course is disused.

Main field of study

Computer Science and Engineering

Course level

First cycle

Course type

Programme course

Examiner

Christer Bäckström

Director of studies or equivalent

Ahmed Rezine

Education components

Preliminary scheduled hours: 22 h
Recommended self-study hours: 31 h
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Period Timetable module Language Campus ECV
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Chinese 7 (Autumn 2017) 2 1 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Chinese (Specialization Computer Science and Engineering) 7 (Autumn 2017) 2 1 Swedish Linköping, Valla C
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - French 7 (Autumn 2017) 2 1 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - French (Specialization Computer Science and Engineering) 7 (Autumn 2017) 2 1 Swedish Linköping, Valla C
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - German 7 (Autumn 2017) 2 1 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - German (Specialization Computer Science and Engineering) 7 (Autumn 2017) 2 1 Swedish Linköping, Valla C
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Japanese 7 (Autumn 2017) 2 1 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Japanese (Specialization Computer Science and Engineering) 7 (Autumn 2017) 2 1 Swedish Linköping, Valla C
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Spanish 7 (Autumn 2017) 2 1 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Spanish (Specialization Computer Science and Engineering) 7 (Autumn 2017) 2 1 Swedish Linköping, Valla C
6CIII Industrial Engineering and Management, M Sc in Engineering 7 (Autumn 2017) 2 1 Swedish Linköping, Valla E
6CIII Industrial Engineering and Management, M Sc in Engineering (Specialization Computer Science and Engineering) 7 (Autumn 2017) 2 1 Swedish Linköping, Valla C

Main field of study

Computer Science and Engineering

Course level

First cycle

Advancement level

G2X

Course offered for

  • Industrial Engineering and Management, M Sc in Engineering
  • Industrial Engineering and Management - International, M Sc in Engineering

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

Programming in Java, basic course in data structures and algorithms.

Intended learning outcomes

After completing the course, the student shall be able to use, explain and analyze data structures and algorithms for representing maps and dictionaries as well as data structures and basic algorithms for graphs.
The further studies in data structures and algorithms shall give the student the opportunity to choose courses from the D and IT programs in year 4.

Course content

Data structures:

  • Advanced tree structures
  • Hash tables
  • Skip lists
  • Graphs
Algorithms:
  • Algorithms for balancing search trees
  • Graph algorithms

Teaching and working methods

Lectures present the theory. Laboratory assignments are mainly computer based, but comprise some small written parts, and integrates theory and gives practical skill.

Examination

LAB1Lab course2 creditsU, G
The course only gives the grades Fail/Pass.

Grades

Two-grade scale, U, G

Other information

Supplementary courses:
Software Engineering 

Department

Institutionen för datavetenskap

Director of Studies or equivalent

Ahmed Rezine

Examiner

Christer Bäckström

Course website and other links

http://www.ida.liu.se/~TDDD71/

Education components

Preliminary scheduled hours: 22 h
Recommended self-study hours: 31 h

Course literature

Additional literature

Books

  • Michael T. Goodrich, Roberto Tamassia, Data Structures and Algorithms in Java
Code Name Scope Grading scale
LAB1 Lab course 2 credits U, G
The course only gives the grades Fail/Pass.

Regulations (apply to LiU in its entirety)

The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.

LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva. 

Additional literature

Books

Michael T. Goodrich, Roberto Tamassia, Data Structures and Algorithms in Java

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize
I U A Modules Comment
1. DISCIPLINARY KNOWLEDGE AND REASONING
1.1 Knowledge of underlying mathematics and science (G1X level)

                            
1.2 Fundamental engineering knowledge (G1X level)
X
X
LAB1

                            
1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)

                            
1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)

                            
1.5 Insight into current research and development work

                            
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
2.1 Analytical reasoning and problem solving
X
X
LAB1

                            
2.2 Experimentation, investigation, and knowledge discovery
X
LAB1

                            
2.3 System thinking

                            
2.4 Attitudes, thought, and learning
X
LAB1

                            
2.5 Ethics, equity, and other responsibilities

                            
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
3.1 Teamwork
X
LAB1

                            
3.2 Communications

                            
3.3 Communication in foreign languages
X

                            
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
4.1 External, societal, and environmental context

                            
4.2 Enterprise and business context

                            
4.3 Conceiving, system engineering and management

                            
4.4 Designing

                            
4.5 Implementing

                            
4.6 Operating

                            
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development

                            
5.2 Economic conditions for knowledge development

                            
5.3 Identification of needs, structuring and planning of research or development projects

                            
5.4 Execution of research or development projects

                            
5.5 Presentation and evaluation of research or development projects

                            

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