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Differentiable programming has found use in a wide variety of areas, particularly scientific computing and machine learning. [5] One of the early proposals to adopt such a framework in a systematic fashion to improve upon learning algorithms was made by the Advanced Concepts Team at the European Space Agency in early 2016.
A differential backup is a type of data backup that preserves data, saving only the difference in the data since the last full backup.The rationale in this is that, since changes to data are generally few compared to the entire amount of data in the data repository, the amount of time required to complete the backup will be smaller than if a full backup was performed every time that the ...
Many programming languages require garbage collection, either as part of the language specification (e.g., RPL, Java, C#, D, [4] Go, and most scripting languages) or effectively for practical implementation (e.g., formal languages like lambda calculus). [5] These are said to be garbage-collected languages.
The Computer Language Benchmarks Game site warns against over-generalizing from benchmark data, but contains a large number of micro-benchmarks of reader-contributed code snippets, with an interface that generates various charts and tables comparing specific programming languages and types of tests. [56]
Backup solutions generally support differential backups and incremental backups in addition to full backups, so only material that is newer or changed compared to the backed up data is actually backed up. The effect of these is to increase significantly the speed of the backup process over slow networks while decreasing space requirements.
Main concerns for data differencing are usability and space efficiency (patch size).. If one simply wishes to reconstruct the target given the source and patch, one may simply include the entire target in the patch and "apply" the patch by discarding the source and outputting the target that has been included in the patch; similarly, if the source and target have the same size one may create a ...
In programming language theory, lazy evaluation, or call-by-need, [1] is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which avoids repeated evaluations (by the use of sharing).
The rdiff-backup script maintains a backup mirror of a file or directory either locally or remotely over the network on another server. rdiff-backup stores incremental rdiff deltas with the backup, with which it is possible to recreate any backup point. [33] The librsync library used by rdiff is an independent implementation of the rsync algorithm.