Lesson 4.3.6.1
4.3.6.1 Dijkstra's shortest path algorithm Quiz: AQA Computer Science, Unit 3
20 questions
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Lesson 4.3.6.1, Dijkstra's shortest path algorithm: 20 multiple choice questions for the AQA Computer Science (7517), Unit 3: Fundamentals of algorithms, written with Revision Ninja.
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The 20 questions
-
What is Dijkstra's algorithm used for?
- Searching sorted lists
- Finding shortest paths in a weighted graph
- Compressing data
- Sorting numbers into ascending order by repeatedly swapping them
-
Dijkstra's shortest path algorithm belongs to which category in the specification?
- Sorting
- Optimisation
- Encryption
- Parsing
-
Dijkstra's algorithm requires edge weights to be which kind of values?
- Non-negative
- Integers only
- Negative only
- All equal to 1
-
Which application is a typical use of shortest-path algorithms?
- Hashing a password
- Rendering a font
- Compressing a video file
- Route planning in a satellite navigation system
-
At each step, which node does Dijkstra's algorithm select next?
- The unvisited node with the smallest known distance from the source
- The node with the highest label
- The unvisited node with the largest distance, so the far nodes are reached first
- The node with the most edges
-
The specification says students will not be expected to recall the steps of Dijkstra's algorithm. What is expected instead?
- Understanding the algorithm and being able to trace it
- Coding it from memory in assembly language
- Proving its correctness formally
- Recalling the steps word for word
-
Graph: S-A weight 4, S-B weight 1, B-A weight 2, A-T weight 3, B-T weight 6. What is the shortest distance from S to T?
- 6
- 4
- 7
- 10
-
In the same graph (S-A 4, S-B 1, B-A 2, A-T 3, B-T 6), what is the shortest distance from S to A?
- 3
- 2
- 6
- 4
-
In the same graph, which node is finalised first after the source S?
- B, with tentative distance 1
- All nodes simultaneously
- A, with tentative distance 4
- T, with tentative distance 6
-
On a graph where every edge has weight 1, Dijkstra's algorithm gives the same result as which search?
- Binary search
- Breadth-first search
- Bubble sort
- Depth-first search
-
Graph: S-A weight 2, A-T weight 2, S-T weight 5. What is the shortest distance from S to T?
- 5
- 2
- 4
- 7
-
Why can negative edge weights break Dijkstra's algorithm?
- A finalised node may later have a cheaper route via a negative edge, which is missed
- The algorithm then runs in exponential time
- The algorithm requires all weights to be equal
- Negative numbers cannot be stored in memory, so the weights would overflow the data type
-
Dijkstra's algorithm is an example of which kind of algorithm?
- Greedy
- Randomised
- Brute force
- Backtracking
-
Graph: A-B weight 1, B-C weight 1, C-D weight 1, A-D weight 5. What is the shortest distance from A to D?
- 7
- 3
- 5
- 1
-
During Dijkstra's algorithm the source has distance 0, and a neighbour X is joined to it by an edge of weight 7. What tentative distance does X receive?
- Infinity
- 0
- 7
- 14
-
With a binary heap, what is the usual time complexity of Dijkstra's algorithm on V vertices and E edges?
- O(V^2) only
- O(n) always
- O(2^V)
- O((V + E) log V)
-
Why do satellite navigation systems model roads as weighted graphs?
- Weights are needed for Dijkstra's algorithm to terminate
- Weighted graphs are always smaller
- Roads have different lengths or travel times, so weights represent real costs
- Unweighted graphs cannot store any roads at all, so weights are essential to the map
-
Graph: S-A 1, S-B 4, A-B 2, B-T 1, A-T 6. What is the shortest distance from S to T?
- 5
- 6
- 7
- 4
-
Which statement about Dijkstra's algorithm is correct?
- It always finds the longest path
- It finds shortest paths correctly in all graphs with negative weights
- It only works on trees
- It finds shortest paths from one source to all nodes when all weights are non-negative
-
Why is breadth-first search not adequate when a two-edge path S-B-A costs 3 but the direct edge S-A costs 10?
- It would choose the path with the most edges
- It would choose the direct edge with fewer edges, giving a cost of 10 instead of 3
- It would give a cost of 13
- It cannot visit node A
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