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List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.
Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
modified_identifier_list «As «non_array_type««array_rank_specifier»» (multiple declarator); valid declaration statements are of the form Dim declarator_list , where, for the purpose of semantic analysis, to convert the declarator_list to a list of only single declarators:
Technically, Perl does not have a convention for including block comments in source code, but POD is routinely used as a workaround. PHP. PHP supports standard C/C++ style comments, but supports Perl style as well. Python. The use of the triple-quotes to comment-out lines of source, does not actually form a comment. [19]
Imperative programming – explicit statements that change a program state; Logic programming – uses explicit mathematical logic for programming; Metaprogramming – writing programs that write or manipulate other programs (or themselves) as their data, or that do part of the work at compile time that would otherwise be done at runtime
The example above, of list comprehension in the sin() function, is a useful feature in of itself. By using implicit parallelism, languages effectively have to provide such useful constructs to users simply to support required functionality (a language without a decent for loop, for example, is one few programmers will use).
Loop-level parallelism is a form of parallelism in software programming that is concerned with extracting parallel tasks from loops.The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures.
If an intersection (in the United States) is represented in data by the zip code (5-digit number) and two street names (strings of text), bugs may appear when a city where streets intersect multiple times is encountered. While this example may be oversimplified, restructuring of data is a fairly common problem in software engineering, either to ...