Examination arrangement

Course content

The course will cover the following topics:

• Basic principles of object-oriented design and object-oriented programming (OOP) - definitions and concepts in OOP (classes, objects, encapsulation)
• Modelling - Datatypes, logical conditions, loops, logical and arithmetic operations, read and write operations
• Arrays, lists and collections
• Interaction between objects
• Lambda expressions, streams and functional programming
• Debugging and unit-testing
• Introduction to Integrated Development Environment (IDE)

Learning outcome

Knowledge

Candidate:

• can demonstrate knowledge in OOP.
• can explain what a software program is.
• has knowledge of principles such as encapsulation, modularization and interaction of objects within object-oriented programming.
• can explain the concepts of modular architecture and its importance in software program design.
• can explain good design practices such as coupling and cohesion.
• has knowledge of typical life cycles of software design at a high level (design, development and testing).
• can model a class diagram for a given problem and can create basic UML diagrams (e.g., activity diagram, class diagram, sequence diagram, package diagrams).

Skills

Candidate:

• can set up a programming environment to develop, test and run object-oriented programs
• can create structured and well-documented code based on principles of good design practices
• can make use of classes, controls and interaction between objects
• can reuse classes from existing libraries and find relevant classes in API documents
• can apply basic object-oriented programming paradigms to analyse and solve simple problems.
• can apply functional programming
• can test and analyse software programs through unit-testing
• can use an Integrated Development Environment (IDE) and debugger along with other tools to assure the quality of code
• can apply the concepts of version control and actively use it (theory taught in IDATA1004)

General competence

Candidate:

• can explain and make use of knowledge for solving problems in simple application scenarios and across different topics.

Learning methods and activities

Teaching activities every week:

• Lectures with student active learning forms such as livecoding of programming exercises with students.
• Guided lab sessions will be conducted with teaching assistants with individual mentoring and assignment solving.

Mandatory assignments: Mandatory assignments will be provided and 90 % of the assignments must be approved to qualify for the final exam.

Compulsory assignments

• Mandatory assignments

Further on evaluation

A portfolio assessment provides the basis for a final grade in the course. The folder includes a project and a reflection report. Feedback is given during the semester on the contents of the portfolio. In the event of voluntary repetition, failure or valid absence, the entire folder must be retaken for the subsequent completion of the course.

Specific conditions

Recommended previous knowledge

None

Required previous knowledge

Candidate must be admitted to Bachelor in computer science at NTNU

Course materials

Will be provided at the start of the course.

Credit reductions