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  2. B-tree - Wikipedia

    en.wikipedia.org/wiki/B-tree

    A B-tree of depth n+1 can hold about U times as many items as a B-tree of depth n, but the cost of search, insert, and delete operations grows with the depth of the tree. As with any balanced tree, the cost grows much more slowly than the number of elements.

  3. Boxing (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Boxing_(computer_programming)

    However, the compiler automatically transforms the code so that the list will "silently" receive objects, while the source code only mentions primitive values. For example, the programmer can now write list. add (3) and think as if the int 3 were added to the list; but, the compiler will have actually transformed the line into list. add (new ...

  4. B+ tree - Wikipedia

    en.wikipedia.org/wiki/B+_tree

    The order or branching factor b of a B+ tree measures the capacity of interior nodes, i.e. their maximum allowed number of direct child nodes. This value is constant over the entire tree. For a b-order B+ tree with h levels of index: [citation needed] The maximum number of records stored is =

  5. Fibonacci heap - Wikipedia

    en.wikipedia.org/wiki/Fibonacci_heap

    When a second child is cut, the node itself needs to be cut from its parent and becomes the root of a new tree (see Proof of degree bounds, below). The number of trees is decreased in the operation delete-min, where trees are linked together. As a result of a relaxed structure, some operations can take a long time while others are done very ...

  6. Binary expression tree - Wikipedia

    en.wikipedia.org/wiki/Binary_expression_tree

    Next, c, d, and e are read. A one-node tree is created for each and a pointer to the corresponding tree is pushed onto the stack. Creating a one-node tree. Continuing, a '+' is read, and it merges the last two trees. Merging two trees. Now, a '*' is read. The last two tree pointers are popped and a new tree is formed with a '*' as the root ...

  7. 2–3–4 tree - Wikipedia

    en.wikipedia.org/wiki/2–3–4_tree

    If a large proportion of the elements of the tree are deleted, then the tree will become much larger than the current size of the stored elements, and the performance of other operations will be adversely affected by the deleted elements. When this is undesirable, the following algorithm can be followed to remove a value from the 2–3–4 tree:

  8. Code generation (compiler) - Wikipedia

    en.wikipedia.org/wiki/Code_generation_(compiler)

    This second phase does not require a tree traversal; it can be done linearly, and typically involves a simple replacement of intermediate-language operations with their corresponding opcodes. However, if the compiler is actually a language translator (for example, one that converts Java to C++ ), then the second code-generation phase may ...

  9. Shift-reduce parser - Wikipedia

    en.wikipedia.org/wiki/Shift-Reduce_Parser

    Shift-reduce parse tree built bottom-up in numbered steps. Consider the string A = B + C * 2. At step 7 in the example, only "A = B +" has been parsed. Only the shaded lower-left corner of the parse tree exists. None of the parse tree nodes numbered 8 and above exist yet.