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What is sand heap analogy?

Updated: 10/19/2022
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A formal identity between the differential equation and boundary conditions for a stress function for torsion of a perfectly plastic prismatic bar, and those for the height of the surface of a granular material, such as dry sand, which has a constant angle of rest. Also known as sand hill analogy

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What are stored in heap memory?

Objects are stored in heap.


What is Fibonacci heaps algorithm?

fibonacci heap is a heap


In Java where do instance variables stored in memory?

An instance variable is part of an object. Therefore, it gets stored together with the object, on the heap. The heap is the part of memory which is used to store objects.An instance variable is part of an object. Therefore, it gets stored together with the object, on the heap. The heap is the part of memory which is used to store objects.An instance variable is part of an object. Therefore, it gets stored together with the object, on the heap. The heap is the part of memory which is used to store objects.An instance variable is part of an object. Therefore, it gets stored together with the object, on the heap. The heap is the part of memory which is used to store objects.


Average complexity of heap short algorithm?

The average heap short complexity is O(log n)


Difference between Fibonacci heap and binomial heap?

Both Binomial Heap and Fibonacci Heap are types of priority queues, but they have some differences in their structure and performance characteristics. Here's a comparison between the two: Structure: Binomial Heap: Binomial Heap is a collection of Binomial Trees. A Binomial Tree is a specific type of tree with a recursive structure. Each Binomial Tree in a Binomial Heap has a root node and may have children, where each child is also a root of a Binomial Tree of smaller size. Fibonacci Heap: Fibonacci Heap is a collection of trees, similar to Binomial Heap, but with more flexible tree structures. It allows nodes to have any number of children, not just two as in the Binomial Heap. The trees in a Fibonacci Heap are not strictly binomial trees. Operations Complexity: Binomial Heap: Binomial Heap supports the following operations with the given time complexities (n is the number of elements in the heap): Insertion: O(log n) Find minimum: O(log n) Union (merge): O(log n) Decrease key: O(log n) Deletion (extract minimum): O(log n) Fibonacci Heap: Fibonacci Heap generally has better time complexities for most operations (amortized time complexity). The amortized analysis takes into account the combined cost of a sequence of operations. For Fibonacci Heap (n is the number of elements in the heap): Insertion: O(1) Find minimum: O(1) Union (merge): O(1) Decrease key: O(1) Deletion (extract minimum): O(log n) Potential Advantage: Fibonacci Heap: The main advantage of Fibonacci Heap is that it allows constant-time insertion, decrease key, and deletion operations in the amortized sense. This makes it particularly useful in certain algorithms, such as Dijkstra's algorithm for finding the shortest path in a graph, where these operations are frequently used. Space Complexity: Binomial Heap: Binomial Heap usually requires more memory due to the strict structure of Binomial Trees. Fibonacci Heap: Fibonacci Heap can have better space complexity due to its more flexible structure, but this can vary depending on the specific implementation. Real-world Use: Binomial Heap: Binomial Heap is simpler to implement and may be preferred when ease of implementation is a concern. Fibonacci Heap: Fibonacci Heap's advantage in amortized time complexity makes it a better choice in scenarios where frequent insertions, deletions, and decrease key operations are expected. In summary, Binomial Heap and Fibonacci Heap are both priority queue data structures, but Fibonacci Heap offers better amortized time complexity for certain operations. However, Fibonacci Heap can be more complex to implement and may require more memory than Binomial Heap in some cases. The choice between the two depends on the specific use case and the performance requirements of the application.