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Leaving Cert Applied Maths: Greedy vs dynamic algorithms

How often Greedy vs dynamic algorithms comes up on the Applied Maths papers, every year it was asked, and questions to try.

HL Asked on 1 of the last 3 Higher Level papers, most recently in 2024.

Greedy vs dynamic algorithms, Higher Level(7 marks)

Quick ones on Greedy vs dynamic algorithms.

(a)What makes an algorithm greedy?
  1. It works backwards from the final stage
  2. It takes the best-looking choice at each step
  3. It checks every possible route in turn
(b)Which algorithm can find the maximum-profit route through a staged network?
  1. Kruskal's (spanning tree)
  2. Dijkstra's (shortest path)
  3. Bellman's (dynamic programming)
(c)Justifying an algorithm by optimality means showing that it…?
  1. Always gives the best possible solution
  2. Runs in the fewest possible steps
  3. Always gives a valid, workable solution
Show the answers

(a) It takes the best-looking choice at each step

(b) Bellman's (dynamic programming)

(c) Always gives the best possible solution

Your turn: Higher Level questions on Greedy vs dynamic algorithms.

Higher Level

Asked on 1 of the last 3 Higher Level papers, most recently in 2024.

Every paper, year by year

YearWhere it came up
2025Not asked
2024Q8
2023Not asked

Links open the State Examinations Commission’s paper for that year.

More Greedy vs dynamic algorithms questions

Greedy vs dynamic algorithms, 3 marks

Justifying an algorithm by correctness means showing that it…?

  1. Always gives the cheapest possible solution
  2. Uses the fewest possible steps
  3. Always ends with a valid solution of the right type
Show the answer

Always ends with a valid solution of the right type

Correctness: the output is a genuine answer, e.g. Kruskal always ends with a spanning tree. Optimality is the separate claim that no valid answer is better.

Other Applied Maths topics

All of Leaving Cert Applied Maths