Explain Dijkstra vs A*.
Dijkstra’s algorithm finds the shortest path in a graph by exploring all possible routes, while A* improves it by using a heuristic to guide the search toward the goal faster.
When to Use
Use Dijkstra when you need a guaranteed shortest path and no heuristic (like GPS routing or network latency mapping). Use A* when you can estimate the distance to the goal—common in game pathfinding, AI navigation, and map search systems.
Example
Imagine navigating a city: Dijkstra explores every street, while A* focuses on those leading closer to your destination using a heuristic like straight-line distance.
To master such algorithms, explore Grokking Data Structures & Algorithms for Coding Interviews, Grokking System Design Fundamentals, Grokking the Coding Interview, or Mock Interviews with ex-FAANG engineers.
Why Is It Important
A strong grasp of Dijkstra vs A* helps you reason about efficiency vs accuracy, critical in interviews and real-world systems like routing engines or logistics optimization.
Interview Tips
Say “A* is Dijkstra plus a heuristic.” Emphasize A*’s performance gain and Dijkstra’s completeness.
Walk through a simple map example to show your understanding.
Trade-offs
Dijkstra is slower but reliable. A* is faster but depends on a good heuristic—if it’s poor, performance drops.
Pitfalls
Avoid assuming A* is always better. If your heuristic overestimates, it can miss the optimal path. Always ensure heuristic admissibility for correctness.
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