ENAI13-301: Software Design, Maintenance and AI integration

Description

This subject provides an overview of software engineering principles, focusing on the design, maintenance, and evolution of software systems in modern development environments. Students will explore the software development life cycle, foundational design concepts, and the importance of modularity, testing, validation, and version control. Emphasis is placed on quality assurance practices and the use of tools to support collaborative development. The subject also introduces AI-integrated approaches to software design and maintenance, examining how AI tools can assist in code generation, refactoring, testing, and documentation. Through practical exercises and critical analysis, students will gain the skills to design robust software systems and integrate AI tools effectively and ethically into the software engineering workflow.

Subject details

Type:	Undergraduate Subject
Code:	ENAI13-301
Faculty:	Bond Business School
Credit:	10
Study areas:	Business, Commerce, and Entrepreneurship

Learning outcomes

Explain key software engineering principles and development life cycle models in the context of designing maintainable and scalable systems.
Explain modular software architectures that support maintainability, extensibility, and collaborative development.
Apply testing, validation, and quality control techniques to ensure software reliability.
Use version control tools to manage code changes and support team-based development.
Use AI tools to assist in software design and maintenance processes and identify their benefits and limitations in programming workflows.

Enrolment requirements

Requisites:	Nil
Assumed knowledge:	Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge. Assumed Prior Learning (or equivalent): ENAI11-100: Computational Thinking ENAI11-102: Algorithms and Data Structures with AI-Assisted Implementation
Restrictions:	This subject is not available as a general elective. To be eligible for enrolment, the subject must be specified in the students’ program structure.

Requisites:

Nil

Assumed knowledge:

Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.

Assumed Prior Learning (or equivalent):

Restrictions:

This subject is not available as a general elective. To be eligible for enrolment, the subject must be specified in the students’ program structure.