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MAT1101 Discrete Mathematics for Computing

Semester 1, 2023 Online
Units : 1
School or Department : School of Mathematics, Physics & Computing
Grading basis : Graded
Course fee schedule : /current-students/administration/fees/fee-schedules

Staffing

Course Coordinator:

Overview

Discrete methods underlie the areas of data structures, computational complexity and the analysis of algorithms. Continuing advances in technology - particularly in applications of computing - have enhanced the importance of discrete (or finite) mathematics for understanding not only the foundations of computer science but also the basis on which computational solutions to a wide variety of applications problems rests.

This course introduces the basic elements of discrete mathematics which provide a foundation for an understanding of algorithms and data structures used in computing. Topics covered include number systems, logic, relations, functions, induction, recursion, Boolean algebra and graph theory.

Course learning outcomes

On successful completion of this course students will be able to:

  1. Recognise and understand how numeric and character data is stored in a computer
  2. Interpret and write simple algorithms in pseudo-code
  3. Recognise and analyse basic graphs and trees
  4. Effectively use symbolic logic, to implement mathematical reasoning and construct proofs
  5. Effectively communicate discrete mathematical concepts and arguments using appropriate mathematical notation

Topics

Description Weighting(%)
1. Computer representation of character and numeric data. Binary and hexadecimal system. ASCII code. Integer and floating-point representations. 25.00
2. Functions and algorithms. Pseudo-code for binary/decimal and other conversions. Control structures for iteration and branching. Recursive functions. Proof by induction. 25.00
3. Truth tables and the laws of logic. Venn diagrams. Ordering and equivalence relationships. Digital circuits and Boolean algebra. Logical reduction and Karnaugh maps. 25.00
4. Graphs and trees. Eulerian and Hamiltonian graphs. Spanning trees. Dijkstra's and Prim's algorithms. Expression trees. Huffman codes. 25.00

Text and materials required to be purchased or accessed

Grossman, Peter 2009, Discrete Mathematics for Computing, 3rd edn, Palgrave MacMillan, Basingstoke, New York.
A scientific calculator.
All other study materials are available only from the course website which can be accessed through the UniSQ 精东传媒appDesk.

Student workload expectations

To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.

Assessment details

Approach Type Description Group
Assessment
Weighting (%) Course learning outcomes
Assignments Written Quiz No 10 1,2
Assignments Written Mathematical Analysis 1 No 30 1,2,5
Assignments Written Mathematical Analysis 2 No 30 4,5
Assignments Written Mathematical Analysis 3 No 30 1,2,3,4,5
Date printed 9 February 2024