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# Difference between binary search tree and heap tree?

###### Answered 2010-10-11 00:08:22

A binary search tree uses the definition: that for every node,the node to the left of it has a less value(key) and the node to the right of it has a greater value(key).

Where as the heap,being an implementation of a binary tree uses the following definition:

If A and B are nodes, where B is the child node of A,then the value(key) of A must be larger than or equal to the value(key) of B.That is,

key(A) ≥ key(B).

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## Related Questions

The difference between Binomial heap and binary heap is Binary heap is a single heap with max heap or min heap property and Binomial heap is a collection of binary heap structures(also called forest of trees).

a heap is a big amount of something and bin is the first name of a terrorist

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Both insertion sort and heap sort are in-place sorting techniques( ie they dont require addition memory space). The main difference between these two techniques is in their efficiency. Insertion sort has an efficiency of O(n2) while heap sort has an efficiency of O(n*log n). Hence heap sort is faster.

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fibonaccci heap work as a circular link list while binomial heap does not work as a circular link list........

A compost heap is a pile of composting material that is in a pile on the ground. A compost pit is dug into the ground and the composting material is placed in it.

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Rotten ones will be mushy. slimy, and smell like a compost heap.

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A binary heap is defined as follows: # It it an "almost" complete binary tree. That is, the bottom level of a heap of height h is partially filled from left to right, and may only have from 1 to 2h nodes. This may make some of the nodes at level h-1 into leaf nodes. So a binary heap of height h may have anywhere from 2h to 2h+1-1 nodes. # It satisfies the heap property. Each node has some ordered value associated with it, like a real number. The heap property asserts that a parent node must be greater than or equal to both of its children. A binary heap is easily represented using an array, let's call it A[1..length(A)]. The size of the heap will be called heap-size(A) (obviously heap-size(A) length(A)). We can use the first element of the array, element #1, as the root of the heap. The left child of array element i is at element 2i, and the right child is at element 2i+1. Also, the parent of an element at node i is at half of i. An element can tell whether it is a left or right child simply be checking whether it is even or odd, respectively. We define these "algorithms" for finding indices parents and children in pseudocode: Parent (i) return floor (i / 2) Left (i) return 2 * i Right (i) return 2 * i + 1 You can tell if an array element i is in the heap simply by checking whether i heap-size(A). Note: this scheme doesn't work in general with binary (possibly incomplete) trees, since representing leaf nodes at depths less than the height of the tree minus 1 isn't possible, and if it were, it would waste space. This representation of an almost complete binary tree is pretty efficient, since moving around the tree involves multiplying and dividing by two, operations that can be done with simple shifts in logic, and adding one, another simple instruction. Asymptotically speaking, each of the heap node access functions above consume O(1) time. ghjghjhjk hjkjk

Answer:- A sorting algorithm that works by first organizing the data to be sorted into a special type of binary tree called a heap. The heap itself has, by definition, the largest value at the top of the tree, so the heap sort algorithm must also reverse the order. It does this with the following steps:1. Remove the topmost item (the largest) and replace it with the rightmost leaf. The topmost item is stored in an array.2. Re-establish the heap.3. Repeat steps 1 and 2 until there are no more items left in the heap.The sorted elements are now stored in an array.A heap sort is especially efficient for data that is already stored in a binary tree. In most cases, however, the quick sort algorithm is more efficient.GOURAV KHARE (CHANDIGARH)gouravsonu89@gmail.com

The stack is a local memory reserve where the program stores variable and function data. The heap is a special memory reserve where the programmer can dynamically allocate memory from. The heap is useful when the programmer doesn't know how large to make certain variables, he just constructs one of the right size during run-time.

A compost pit is composting materials put into a pit dug in the ground. A compost heap is when composting materials are placed in a heap on the surface of the ground.

The song actually comes from a verse of "hide and seek" by imogen heap. You can see this video on youtube. Search Imogen Heap - hide and seek So in conclusion u can see that imogen heap would be your best answer.

There are different visions. You can see them on google images if you search for them.

The important difference is that Moraine is a mass of debris carried by glaciers which forms ridges and mounds when deposited. Scree is just an accumulation of weathered mass at the foot of a cliff or on a hillside forming a sloping heap

A level cup is usually made exactly equal with the the brim, (flat) and a heaping cup isn't flattened (has a small heap at the top).

You either turn them over so they compost or you let them grow and use them. It is better to remove potatoes from your compost heap turning them over will make no difference.

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