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Data Structures, 6 credits
Datastrukturer, 6 hp
TND004
Main field of study
Computer Science and Engineering Media Technology and EngineeringCourse level
First cycleCourse type
Programme courseExaminer
Aida NordmanDirector of studies or equivalent
Camilla ForsellEducation components
Preliminary scheduled hours: 60 hRecommended self-study hours: 100 h
ECV = Elective / Compulsory / Voluntary
| Course offered for | Semester | Period | Timetable module | Language | Campus | ECV | |
|---|---|---|---|---|---|---|---|
| 6CIEN | Electronics Design Engineering, M Sc in Engineering | 6 (Spring 2017) | 2 | 3 | Swedish | E | |
| 6CMEN | Media Technology and Engineering, M Sc in Engineering | 6 (Spring 2017) | 2 | 3 | Swedish | C | |
Main field of study
Computer Science and Engineering, Media Technology and EngineeringCourse level
First cycleAdvancement level
G2XCourse offered for
- Electronics Design Engineering, M Sc in Engineering
- Media Technology and Engineering, 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 C++Intended learning outcomes
The aim of the course is to give students the tools to independently be able to create programs that solve practical problems dealing with large amounts of data, taking into account efficient use of time and memory. Upon completion of the course the student should fulfill the following learning outcomes.
- To propose specific data structures and algorithms to address practical problems.
- To motivate objectively the choices made, concerning chosen data structures, and relate to the known scientific results in the field.
- To analyze the trade offs, regarding efficiency in several aspects, of different data structures proposed for addressing a practical problem.
- To implement and use the data structures and algorithms in application programs.
Course content
Algorithm analysis. Recursion. Lists, stacks and queues. Trees and tree traversals. Binary search trees, threaded trees and balanced trees. Hashing and hash tables. Priority queues and binary heaps. Sorting och searching. Indexed files. Graphs and graph traversals. Fundamental graph algorithms.
Teaching and working methods
Lectures, lessons, and laboratory work.
Examination
| LAB1 | Laboratory work | 3 credits | U, G |
| TEN1 | Written examination | 3 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för teknik och naturvetenskapDirector of Studies or equivalent
Camilla ForsellExaminer
Aida NordmanCourse website and other links
http://www2.itn.liu.se/utbildning/kurs/index.html?coursecode=TND004Education components
Preliminary scheduled hours: 60 hRecommended self-study hours: 100 h
Course literature
Data Structure and Algorithm Analysis in C++, Mark Allen Weiss, Addison Wesley, 4th edition, year 2014.| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB1 | Laboratory work | 3 credits | U, G |
| TEN1 | Written examination | 3 credits | U, 3, 4, 5 |
Course literature is preliminary.
Data Structure and Algorithm Analysis in C++, Mark Allen Weiss, Addison Wesley, 4th edition, year 2014.
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) |
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X
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| 1.2 Fundamental engineering knowledge (G1X level) |
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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X
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X
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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X
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| 2.2 Experimentation, investigation, and knowledge discovery |
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X
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X
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| 2.3 System thinking |
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X
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X
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| 2.4 Attitudes, thought, and learning |
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X
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X
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| 2.5 Ethics, equity, and other responsibilities |
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X
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X
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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| 3.2 Communications |
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X
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| 3.3 Communication in foreign languages |
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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| 4.4 Designing |
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| 4.5 Implementing |
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| 4.6 Operating |
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| 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 |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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