A Level Computer Science: Algorithms for Main Data Structures
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All Computer Science topics are covered, and each module comes complete with:
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Frequently Asked Questions
What is the significance of balancing algorithms, such as AVL trees, in the context of binary search trees?
Balancing algorithms like AVL trees ensure that the tree remains balanced, preventing skewed structures and maintaining efficient search, insertion, and deletion operations with a time complexity of O(log n).
How does a hash function contribute to the efficiency of hash tables, and what role does collision resolution play?
A hash function maps keys to indices in the hash table, aiming to distribute values uniformly. Collision resolution mechanisms, like chaining or open addressing, handle cases where multiple keys map to the same index.
Explain the advantage of using a stack in algorithms for parentheses matching.
Stacks provide a Last-In-First-Out (LIFO) structure, making them suitable for tracking and matching parentheses in expressions. An open parenthesis is pushed onto the stack, and when a closing parenthesis is encountered, it is popped, ensuring correct pairing.
How does the Breadth-First Search (BFS) algorithm differ from Depth-First Search (DFS) when traversing a graph?
BFS explores all neighbors of a node before moving on to their neighbors, resulting in a level-by-level exploration. In contrast, DFS goes as deep as possible along each branch before backtracking, creating a depth-first exploration.
What role does a priority queue play in algorithms for heaps, and how is it useful in applications like Dijkstra's algorithm?
A priority queue is often implemented using heaps and facilitates efficient retrieval of the element with the highest or lowest priority. In Dijkstra's algorithm, a priority queue helps select the next vertex with the smallest distance during the exploration of the graph.