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For example, the classic techniques for operator strength reduction insert new computations into the code and render the older, more expensive computations dead. [2] Subsequent dead-code elimination removes those calculations and completes the effect (without complicating the strength-reduction algorithm).
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.
The purpose of the delete algorithm is to remove the desired entry node from the tree structure. We recursively call the delete algorithm on the appropriate node until no node is found. For each function call, we traverse along, using the index to navigate until we find the node, remove it, and then work back up to the root.
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The term dead code has multiple definitions. Some use the term to refer to code (i.e. instructions in memory) which can never be executed at run-time. [1] [2] [3] In some areas of computer programming, dead code is a section in the source code of a program which is executed but whose result is never used in any other computation.
Φ functions are not implemented as machine operations on most machines. A compiler can implement a Φ function by inserting "move" operations at the end of every predecessor block. In the example above, the compiler might insert a move from y 1 to y 3 at the end of the middle-left block and a move from y 2 to y 3 at the
In computing, inline expansion, or inlining, is a manual or compiler optimization that replaces a function call site with the body of the called function. Inline expansion is similar to macro expansion, but occurs during compilation, without changing the source code (the text), while macro expansion occurs prior to compilation, and results in different text that is then processed by the compiler.
Throughout insertion/deletion operations, the K-D-B-tree maintains a certain set of properties: The graph is a multi-way tree. Region pages always point to child pages, and can not be empty. Point pages are the leaf nodes of the tree. Like a B-tree, the path length to the leaves of the tree is the same for all queries.