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
EFTSL:	0.125
Faculty:	Bond Business School
Credit:	10
Study areas:	Business, Commerce, and Entrepreneurship
Subject fees:	Commencing in 2027: $4,810.00 Commencing in 2027: $6,550.00

Learning outcomes

Analyse key software engineering principles and development life cycle models in the context of designing maintainable and scalable systems.
Present modular software architecture solutions that support maintainability, extensibility and collaborative development to a technical audience.
Evaluate testing, validation, and quality control techniques to ensure software reliability and improve business systems.
Use version control tools to manage code changes and support team-based development.
Analyse the role of AI tools in software design, maintenance workflows, their benefits and limitations.
Analyse the ethical and governance implications of design and maintenance decisions in AI-integrated software systems.

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): ENAI11-102: Algorithms and Data Structures with AI-Assisted Implementation ENAI11-100: Thinking with AI
Restrictions:	Nil

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:

Nil