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Level 4 Diploma in Cyber Security

Measuring complexity: Big O notation

CYB404 · Algorithms and Data Structures — Week 3 of 16

CourseCYB404
Week3 of 16
SemesterII
TutorOnline in the course chat

This week’s topics

Measuring complexity: Big O notation

  1. Measuring complexity: Big O and little o notation
  2. Loops, nested loops, recursion and memory usage

What you will be able to do

  • 2.1 Demonstrate an ability to write Big O and little o notation to describe algorithmic complexity.
  • 2.2 Explain the impact of algorithmic design choice on computational complexity for a variety of examples.

Activity

Start with this week’s 2 videos, then: Seminar, guided reading and a short written task: demonstrate an ability to write Big O and little o notation to describe algorithmic complexity.

Study materials

Videos

  • Why My Teenage Code Was Terrible: Sorting Algorithms and Big O Notation · YouTube · Tom Scott · 10 min · for registered students
  • Introduction to Big O Notation · YouTube · Neso Academy · 8 min · for registered students

Further resources

  • Introduction to Computer Science, 3.3: Formal Properties of Algorithms · PDF · OpenStax Introduction to Computer Science (2024), 3.3: time complexity and comparing algorithms (a step up), pp. 104–109 · for registered students
Materials marked “for registered students” open in the student portal, which is set up as soon as you receive final acceptance.
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Admitted students ask questions on this week’s page in the student portal: an AI assistant trained on the course answers first, and during the course’s timetabled classes Connect to your tutor brings your tutor into the chat, who may start a call if needed.

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Course plan
  • Week 1: Data structures: arrays, lists, stacks, queues, sets and di…
  • Week 2: Choosing data structures, with a Python refresher
  • Week 3: Measuring complexity: Big O notation
  • Week 4: Problem classes: computability and Turing machines, P and N…
  • Week 5: Recursion and memoisation (e.g. Tower of Hanoi); the memory…
  • Week 6: Algorithmic paradigms: divide and conquer, backtracking, gr…
  • Week 7: Sort, search and pathfinding algorithms compared by time an…
  • Midterm: Midterm evaluation
  • Week 9: Writing pseudocode as a universal template for algorithms
  • Week 10: Checking algorithms are correct: tracing, testing and timing
  • Week 11: Debugging and testing implementations; review and practice …
  • Week 12: Applying Algorithms and Data Structures in practice: case s…
  • Week 13: Assignment workshop: research, planning and referencing
  • Week 14: Assignment workshop: drafting, feedback and improvement
  • Week 15: Review and coursework completion
  • Final: Final assessment and submission
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