FIT3155 - Advanced data structures and algorithms - 2019

6 points, SCA Band 2, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.


Information Technology

Chief examiner(s)

Dr Arun Konagurthu

Unit guides



  • First semester 2019 (On-campus)
  • Second semester 2019 (On-campus)


  • First semester 2019 (On-campus)
  • Second semester 2019 (On-campus)




This unit builds on the concepts learnt in introductory algorithms and data structures study. It covers advanced algorithmic paradigms and problem-solving techniques required to address real-world programming challenges. It explores, in depth, the design and analysis of space-efficient data structures and time-efficient problem solving strategies to be used with them. Topics include amortized analysis, advanced sorting and searching algorithms, new tree/string/graph data structures and algorithms, and number-theoretic algorithms amongst others.


At the completion of this unit, students should be able to:

  1. analyse efficient data structures and effective algorithmic paradigms;
  2. design and implement efficient algorithms and data structures for use on large data sets;
  3. apply advanced algorithms and data structures to tackle complex computational problems;
  4. prove the correctness of programs and reason about their space and time complexities.


NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 60%; In-semester assessment: 40%

Workload requirements

Minimum total expected workload equals 12 hours per week comprising:

  1. Contact hours for on-campus students:
    • Two hours lectures weekly
    • Three hours laboratories/tutorial weekly
  2. Additional requirements (all students):
    • A minimum of 7 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit applies to the following area(s) of study