Course PM

DIT183 and DAT495 data structures and algorithms, V25 lp4 (7.5 hp)

This course is offered by the department of Computer Science and Engineering.

Note: get started with the starting guide!

Teachers and student representatives

See here.

Course purpose

Data structures and algorithms are fundamental building blocks in almost all software products. Knowledge and skills in data abstraction, data structures, and algorithms are important in the construction, use, and maintenance of adaptable, reusable, correct, and efficient program components.

The course gives knowledge and skills in the construction and use of algorithms and data structures, an introduction to various techniques for the analysis of algorithms, and insights in the advantages of using data abstraction in program development.

The following topics are covered by the course:

• abstract data types,
• data structures and algorithms focusing on imperative och object-oriented languages,
• common data structures such as arrays, linked lists, unbalanced and balanced trees, heaps, and hash tables,
• how these can be used to implement abstract data types such as stacks, queues, priority queues, maps, sets, and graphs,
• standard algorithms for these data structures, including their resource demands,
• searching and sorting algorithms,
• using different libraries for data structures and algorithms,
• basic complexity analysis of data structures and algorithms.

Course literature

See here.

Schedule

See TimeEdit.

Course design

We use the following tools to communicate:

• Canvas. General information, announcements, lecture material, exercises, online quizzes.
• Discord. Our primary question and discussion medium. Also used to request lab supervision.
• Chalmers GitLab. The lab projects happen here. Sign in with Chalmers Login.
• Mentimeter. Interactive quizzes during lectures. You can install the app on your phone.
• Zoom. We may offer online lab supervision via Zoom or other video chat services.

The course consists of:

• Lectures
• Laborations
• Exercises and exam preparation

Examination form

To pass the course, you need to pass:

• all four laborations (including supervision checkpoints),
• the written hall exam at the end of the course.

Examination dates

• Lab deadlines
• Exam schedule

Learning objectives and syllabus

Your study portal has the complete syllabus. Below are main intended learning outcomes.

Knowledge and understanding

• explain basic abstract data types and data structures, including lists, queues, hash tables, trees, and graphs,
• explain some of the algorithms used to manipulate and query these data structures in an efficient way, and explain why they are correct,

Competence and skills

• apply basic abstract data types and data structures, and algorithms related to these,
• implement and use abstract data types as interfaces, and data structures as classes, in an object-oriented programming language,
• read, specify, and describe algorithms, at a higher level of abstraction than code,

Judgement and approach

• analyse the efficiency of basic algorithms and data structures,
• make informed choices between different data structures and algorithms for different applications.

Changes made since the last occasion

• The exercise sessions are more focussed on exam preparation.
• We switched from Slack to Discord.