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Top

The top operation accesses the element currently having the highest priority in a priority queue or heap.

How 2 Manning books explain it

Advanced Algorithms and Data Structures

The top operation retrieves the element currently having the highest priority at the top of a priority queue or heap, optionally removing it according to the interface semantics.

How it is used
Uses priority queues to retrieve and remove the currently highest-priority element.
How deep it goes
Explains empty checks, root replacement, push-down repair, and d-ary costs, while deferring full implementation details.
Examples
Demonstrates bug-report scheduling, binary or ternary heap removal, and d-ary branching-factor measurements.
What you can do after
Apply it via a priority queue API or implement it with root replacement and push-down repair.

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Grokking Data Structures

A priority queue top method is an operation that removes and returns the element with the highest priority.

How it is used
Uses top to extract the next item from a priority queue according to priority rather than insertion order.
How deep it goes
Explains the heap implementation through root replacement, child selection, push-down, edge cases, and logarithmic performance.
Examples
Uses a Python heap method, helper methods for child selection and push-down, and a comparison table of priority-queue implementations.
What you can do after
Build a heap-based top operation that handles empty and singleton heaps and restores heap order after removal.

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Related concepts

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