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Type aliasing is a feature in some programming languages that allows creating a reference to a type using another name. It does not create a new type hence does not increase type safety . It can be used to shorten a long name.
Aliasing can occur in any language that can refer to one location in memory with more than one name (for example, with pointers).This is a common problem with functions that accept pointer arguments, and their tolerance (or the lack thereof) for aliasing must be carefully documented, particularly for functions that perform complex manipulations on memory areas passed to them.
In alias analysis, we divide the program's memory into alias classes. Alias classes are disjoint sets of locations that cannot alias to one another. For the discussion here, it is assumed that the optimizations done here occur on a low-level intermediate representation of the program. This is to say that the program has been compiled into ...
Class-based object-oriented programming languages support objects defined by their class. Class definitions include member data. Message passing is a key concept, if not the main concept, in object-oriented languages. Polymorphic functions parameterized by the class of some of their arguments are typically called methods.
An example of spatial aliasing is the moiré pattern observed in a poorly pixelized image of a brick wall. Spatial anti-aliasing techniques avoid such poor pixelizations. Aliasing can be caused either by the sampling stage or the reconstruction stage; these may be distinguished by calling sampling aliasing prealiasing and reconstruction ...
Pages in category "Articles with example Python (programming language) code" The following 200 pages are in this category, out of approximately 201 total. This list may not reflect recent changes .
Predictors like gshare use multiple table entries to track the behavior of any particular branch. This multiplication of entries makes it much more likely that two branches will map to the same table entry (a situation called aliasing), which in turn makes it much more likely that prediction accuracy will suffer for those branches.
Python's runtime does not restrict access to such attributes, the mangling only prevents name collisions if a derived class defines an attribute with the same name. On encountering name mangled attributes, Python transforms these names by prepending a single underscore and the name of the enclosing class, for example: >>>