CSSE1001 — Introduction to Software Engineering

course-info
python

Overview

Introduction to Software Engineering through programming, with a focus on the fundamentals of computing and programming using an exploratory, problem-based approach: building abstractions with procedures, data and objects; data modelling; designing, coding, and debugging programs of increasing complexity. Taught in Python. The GUI module has been removed from the scope of this course to leave more time for fundamentals.

No prior programming knowledge is assumed. Incompatible with COMP1502, CSSE7030, ENGG1001.

Staff

  • Dr Paul Vrbik — course coordinator & lecturer — CSSE1001@eecs.uq.edu.au — office hours by appointment
  • Dr Kasra Khosoussi — lecturer

Textbook, if any, isn’t in the source material yet — add it here if it comes up.

Course structure (by week)

Week Topic
1 Course introduction. Arithmetic, types, and variables in programming.
2 Python memory model and primitive data.
3 Functions and if-statements.
4 While-loops and data.
5 For-loops and list comprehensions.
6 IO, string methods, testing and debugging.
7 Exceptions, scope, and intro to OOP.
8 Dunder methods and representation invariants.
9 Composition and inheritance.
10 Unified Modelling Language.
11 Design patterns and MVC.
12 Recursion.
13 Functional programming. Complexity.

Applied classes (weeks 2-13) and practicals run alongside lectures, giving guided/self-directed practice with demonstrator feedback. 12 formative Ed Lessons tasks (immediate feedback) and Gradescope (immediate feedback on assignment submissions) support self-study.

Learning outcomes

After successfully completing this course you should be able to:

  1. Apply program constructs such as variables, selection, iteration, and sub-routines.
  2. Apply basic object-oriented concepts such as classes, instances, and methods.
  3. Read and analyse code written by others.
  4. Analyse a problem and design an algorithmic solution to it.
  5. Read and analyse a design and translate it into a working program.
  6. Apply techniques for testing and debugging.

Assessment

Assessment Weight Due Covers
Assignment 1 15% 19/09/2025, 3:00pm Weeks 1-4 (functions, lists, tuples, dictionaries, loops, if-statements)
In-semester exam (Saturday) 25% Sat 13 Sep 2025, 7:15pm, 90 min Up to week 5
Assignment 2 20% 24/10/2025, 3:00pm Weeks 1-11
End-of-semester exam 40% End-of-semester exam period (8/11/2025 - 22/11/2025), 120 min Entire course. Hurdle: exam \(\geq\) 45% required for Grade 4 and above.

Both exams are closed-book, identity-verified, in-person, and paper-based (calculator: Casio FX82 series or UQ-approved/labelled calculator only).

Grading formula

With \(A_1, A_2, EM, EF\) as percentages for Assignment 1, Assignment 2, the in-semester exam, and the end-of-semester exam respectively:

\[\text{MARK} = \max(M_1, M_2)\]

where

\[M_1 = 0.15A_1 + 0.20A_2 + 0.25EM + 0.40EF, \qquad M_2 = 0.15A_1 + 0.20A_2 + 0.10EM + 0.55EF\]

So a poor in-semester exam result can be mitigated by a strong final exam.

Assignments are submitted online via Gradescope. Extensions: up to 7 days maximum (in multiples of 24 hours), handled by the school (not the lecturer) — a medical certificate is required, with no exceptions. Work must be received by the deadline, not just transmitted; there is an undisclosed small grace-period buffer so work only a few minutes late isn’t penalised. Beyond that, late assignment submissions receive 0%.

Academic integrity

  • Don’t cheat — penalties are harsh, and detection tools are sophisticated.
  • Students who maximise assessment scores by using ChatGPT, abusing staff support, or cheating typically fail the exam.
  • You may discuss solutions to problems with others, but must not share code — including for assignments.

Course resources

  • IDLE — the IDE officially supported by tutors.
  • Open Help Center (a.k.a. “ITLC”/“EECSLC”) — 78-217 — Mon, Tue, Wed, Fri 10am-4pm.

Setting expectations

  • Lectures are only a first exposure to a topic — you’re expected to do most of your learning by completing assigned tasks, and to revise both before and after lectures.
  • Secondary school vs. university, per the source: 20 weeks / 5 hrs-per-week / 100 hrs instruction / 30 classmates (secondary) vs. 12 weeks / 2 hrs-per-week / 24 hrs instruction / 1000 classmates (this course). Teachers teach you; instructors guide you.
  • Course staff are human — they will sometimes make errors, be terse, and are often sleep-deprived, despite trying hard to provide a good learning experience.
  • How to succeed: (1) practice makes perfect, (2) learn to debug, (3) do well on the exam.

Lectures