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Level 4 Diploma in Cyber Security

Assignment workshop: research, planning and referencing

CYB404 · Algorithms and Data Structures — Week 13 of 16

CourseCYB404
Week13 of 16
SemesterII
TutorOnline in the course chat

This week’s topics

Assignment workshop: research, planning and referencing

  1. Unpacking the assignment brief and criteria
  2. Finding and evaluating sources
  3. Planning and referencing

What you will be able to do

  • 1.1 Describe a data structure.
  • 1.2 Explain a range of linear and non-linear data structures.
  • 1.3 Analyse the impact of the choice of data structure on algorithmic performance.
  • 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.
  • 2.3 Explain the difference between P and NP.
  • 2.4 Evaluate open problems in problem classification and the impacts of future technologies on the difficulty in solving different classes algorithms.
  • 3.1 Use recursion and memoisation as tools to design solutions to problems.
  • 3.2 Describe a range of sort, search, and pathfinding algorithms.
  • 3.3 Explain the trade-off between memory and computational complexity in algorithmic design.
  • 3.4 Critically analyse algorithmic paradigms such as the greedy approach and divide and conquer approach.
  • 3.5 Evaluate sort, search, and pathfinding algorithms in terms of their space and time complexity.
  • 4.1 Explain how to write pseudo-code for algorithmic design.
  • 4.2 Implement pseudocode in a programming language.
  • 4.3 Evaluate the correctness and speed of an algorithm.
  • 4.4 Use debugging to correct errors in algorithmic implementation.

Activity

Plan the unit assignment against every criterion; source and reference the evidence.

Study materials

Further resources

  • Foundations of Information Systems, 9.2: Project objectives and schedule · PDF · OpenStax Foundations of Information Systems (2025), 9.2 on defining objectives, deliverables and scope and developing a schedule (a step up), pp. 348–349 · for registered students
  • Writing Guide, 14.1: Primary, Secondary and Tertiary Sources · PDF · OpenStax Writing Guide with Handbook (2021), 14.1 on primary and secondary sources (CRAAP test on p. 458), pp. 451–455 · for registered students
  • Questioning CRAAP: a comparison of source evaluation methods with first-year undergraduat… · Open-access article · Lowe et al. (2021), Journal of the Scholarship of Teaching and Learning. Tests the CRAAP checklist against other source-evaluation methods. · 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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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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