HSC Software Engineering

Designing algorithms, working with data and writing, testing and debugging code.

• Software development steps: requirements, design, development, testing and maintenance
• Designing algorithms with sequence, selection and iteration
• Divide and conquer and backtracking
• Pseudocode, flowcharts and structure charts
• Number systems and two's complement
• Data types, data dictionaries and data structures
• Converting algorithms to code with subprograms and parameters
• Waterfall and Agile approaches
• Testing, debugging tools and test data
• Syntax, logic and runtime errors

• The elif Ladder and Logical Conditions
• Defining and Calling Functions
• Dictionaries: Key-Value Mapping
• Tracing code by hand and with print

Modelling problems with classes and objects, and working together on code.

• Objects, classes, encapsulation and abstraction
• Inheritance, generalisation and polymorphism
• Class diagrams, structure charts and flow diagrams
• Message-passing between objects
• Designing and implementing programs with branching, iteration and functions
• Stubs and one logical task per subroutine
• Unit, subsystem and system testing
• Black, white and grey box testing
• Collaborative development and version control

• Classes, Instances and the self Parameter
• The @property Decorator and Setters
• Single Inheritance and Method Overriding
• Has-a versus Is-a: Why Prefer Composition

Programming mechatronic systems: sensors, actuators and control algorithms.

• Applications of mechatronic systems
• Microcontrollers, the CPU, instruction sets and registers
• Sensors, actuators and end effectors
• Wiring diagrams for data and power
• Control algorithms for open and closed loop systems
• Algorithms for autonomous control
• Building a mechatronic system for a real-world problem
• Simulations to test code
• Unit testing control algorithms

Covered in 1:1 mentoring sessions

Designing and building software that protects users and data.

• Benefits of secure software
• Applying the development steps to write secure code
• Security concepts: confidentiality, integrity, availability, authentication and authorisation
• Cryptography and sandboxing
• Privacy-by-design
• Testing security and resilience
• Code review, static and dynamic testing and penetration testing
• Defensive input handling: validation, sanitisation and error handling
• Broken authentication, cross-site scripting and cross-site request forgery
• Social, ethical and legal issues

• Password Hashing
• Roles and Permissions
• Common Attacks and Fixes

How the web works and how web applications are built.

• Applications of web programming and progressive web apps
• How data moves across the internet: packets, IP addresses and DNS
• Web protocols and ports: HTTP, HTTPS, TCP/IP and TLS
• Securing the web: certificates, encryption and digital signatures
• Client-side and server-side programming
• Back-end request handling with web frameworks and databases
• SQL queries: SELECT, WHERE, GROUP BY and joins
• CSS design and cross-device flexibility
• Accessible, inclusive UI and UX
• Version control, libraries and frameworks

• HTTP Methods and Status Codes
• Resources and URLs
• Routes and Parameters
• SELECT columns and aliases

How machine learning and artificial intelligence support automation, and how to program with them.

• Automation with DevOps, robotic process automation and business process automation
• Supervised, unsupervised, semi-supervised and reinforcement learning
• Decision trees and neural networks
• Linear, polynomial and logistic regression models
• K-nearest neighbour
• Applying neural network models with an object-oriented approach
• Impacts of automation on individuals, society and the environment
• Human and dataset bias in AI solutions

• JSON Files with the json Module

Planning, building, documenting and evaluating a substantial software project.

• Defining and analysing a problem and its requirements
• Idea-generation and design tools
• Comparing Waterfall, Agile and WAgile approaches
• Project management with Gantt charts
• Communicating with clients
• Designing, constructing and implementing a solution
• Backups and version control
• Test plans, path and boundary testing
• Responding to feedback and evaluating the solution

• Your first repository and commit
• A Clean Python Project Others Can Run

Preparing for the online HSC exam.

• The computer-based exam: 2 hours 30 minutes including reading time
• Objective-response questions
• Short-answer questions
• Reading Python code in the exam
• Command terms
• Timed practice papers
• Reviewing mistakes

Covered in 1:1 mentoring sessions