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persistent data structures造句

例句與造句

  1. One primary advantage to using purely persistent data structures is that they often behave better in multi-threaded environments.
  2. In general, having inefficient operations is not acceptable for persistent data structures, because this inefficient operation can be called many times.
  3. In general, having innefficient operations is not acceptable for persistent data structures, because this inneficient operation can be called many times.
  4. Ctries support a lock-free, linearizable, constant-time snapshot operation, based on the insight obtained from persistent data structures.
  5. Purely functional data structures are persistent data structures that completely avoid the use of mutable state, but can often still achieve attractive amortized time complexity bounds.
  6. It's difficult to find persistent data structures in a sentence. 用persistent data structures造句挺難的
  7. Persistent data structures can also be created using in-place updating of data and these may, in general, use less time or storage space than their purely functional counterparts.
  8. Alternatively, as in the following Python example, we can reconstruct all ancestors of the inserted node; any reference to the original tree root remains valid, making the tree a persistent data structure:
  9. In particular, if a new node is added at the beginning of a list, the former list remains available as the tail of the new one  a simple example of a persistent data structure.
  10. Red black trees are also particularly valuable in functional programming, where they are one of the most common persistent data structures, used to construct associative arrays and sets which can retain previous versions after mutations.
  11. There also exist persistent data structures which use destructive operations, making them impossible to implement efficiently in purely functional languages ( like Haskell outside specialized monads like state or IO ), but possible in languages like C or Java.
  12. For example, the implementation of set union in the OCaml standard library in theory is asymptotically faster than the equivalent function in the standard libraries of imperative languages ( e . g ., C + +, Java ) because the OCaml implementation exploits the immutability of sets to reuse parts of input sets in the output ( see persistent data structure ).

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