TND004 · 6 credits · Basic level (G2F) · Datateknik, Medieteknik
Data Structures
Active · next start VT 2027
50%
passed the latest ordinary exam
TEN1 · 2 Jun 2026 · 34 students
58%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 243 students
86%
Harder than 86% of courses at basic level
Compared with 874 courses at the same level, ordinary exams over the last three academic years. 70 students.
Part of 2 programmes
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
58% passed · 243 students
- 50%34
- 58%36
- 50%54
- 53%57
- 73%62
Re-exams
57% passed · 122 students
- 44%18
- 80%5
- 71%14
- 20%5
- 74%19
- 63%19
- 50%14
- 43%14
- 50%14
- Pass the re-exam: 57% (122 students), compared with 58% (243 students) on the ordinary exam
- Get 4 or 5: 3% (365 students)
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 67%3
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory work
- G
Main rounds
100% passed · 223 students
- 100%31
- 100%39
- 100%48
- 100%45
- 100%60
Later rounds
No sittings with at least 5 students.
Show small sittings (3)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
- 100%2
About the course
Aim
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, considering efficient use of time and memory. Upon completion of the course the student should fulfill the following learning outcomes.
- To understand fundamental data structures concepts.
- To apply data structures to solve computational problems considering given requirements.
- To analyze and evaluate various data structures in solving computational problems with respect to efficiency and appropriateness.
- To implement and use the data structures and algorithms in application programs.
Content
Algorithm analysis. Recursion. Lists, stacks and queues. Trees and tree traversals. Binary search trees and balanced trees. Hashing and hash tables. Priority queues and binary heaps. Sorting och searching. Graphs and graph traversals. Fundamental graph algorithms.
- Examiner
- Aida Nordman
- Scheduled hours
- 60 h
- Main field of study
- Datateknik, Medieteknik