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Level 4 Diploma in Cyber Security

Algorithmic paradigms: divide and conquer, backtracking, greedy algorithms and dynamic programming

CYB404 · Algorithms and Data Structures — Week 6 of 16

CourseCYB404
Week6 of 16
SemesterII
TutorOnline in the course chat

This week’s topics

Algorithmic paradigms: divide and conquer, backtracking, greedy algorithms and dynamic programming

  1. Starting point: decomposition and merge sort
  2. Algorithmic paradigms such as the greedy approach and divide and conquer approach

What you will be able to do

  • 3.4 Critically analyse algorithmic paradigms such as the greedy approach and divide and conquer approach.

Activity

Start with this week’s 2 videos, then: Seminar, guided reading and a short written task: critically analyse algorithmic paradigms such as the greedy approach and divide and conquer approach.

Study materials

Videos

  • Merge sort · Oak National Academy, Key Stage 4 (GCSE level) · for registered students
  • Computational Thinking · YouTube · Computer Science Lessons · 14 min · for registered students

Further resources

  • Introduction to Computer Science, 3.2: Algorithm Design and Discovery · PDF · OpenStax Introduction to Computer Science (2024), 3.2: designing an algorithm and checking how it behaves, pp. 97–103 · for registered students
  • Introduction to Computer Science, 2.1: Computational Thinking · PDF · OpenStax Introduction to Computer Science (2024), 2.1: decomposition, algorithms, pseudocode and flowcharts (figures from p. 46), pp. 40–51 · for registered students
  • Computational thinking · Open-access article · Wing (2006), Communications of the ACM. The short classic essay on thinking algorithmically before coding. · 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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