{"id":5152,"date":"2017-01-28T20:48:10","date_gmt":"2017-01-28T20:48:10","guid":{"rendered":"https:\/\/www.modernescpp.com\/index.php\/immutable-data\/"},"modified":"2024-07-22T16:31:13","modified_gmt":"2024-07-22T16:31:13","slug":"immutable-data","status":"publish","type":"post","link":"https:\/\/www.modernescpp.com\/index.php\/immutable-data\/","title":{"rendered":"Immutable Data"},"content":{"rendered":"

A key to purely functional languages is that their data are immutable. Therefore, assignments such as x= x+1<\/span> or ++x<\/span> are not possible in the purely functional language Haskell. The consequence is that Haskell supports no loops like for,<\/span> while,<\/span> or until.<\/span> They are based on the modification of a loop variable. Haskell does not modify existing data; Haskell creates new data when needed and reuses the old ones.<\/p>\n

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Immutable data<\/h2>\n

\"CharakteristikeImmutableDataEng\"<\/p>\n

Immutable data has a lovely property. They are implicitly thread-safe because they miss a necessary condition for a data race.<\/a> A data race is a state, in which at least two threads access shared data at the same time, and at least one of the threads is a writer.<\/p>\n

Quicksort in Haskell<\/h3>\n

The quicksort algorithm in Haskell shows the immutability of data very nicely.<\/p>\n

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qsort []<\/span> =<\/span> []<\/span>\nqsort (x:<\/span>xs) =<\/span> qsort [y | y <-<\/span> xs, y < x] ++ [x] ++ qsort [y | y <-<\/span> xs, y >= x]\n<\/pre>\n<\/div>\n
The quicksort algorithm qsort<\/span> consists of two function definitions. The quicksort will be applied to the empty list in the first line. Of course, the result is an empty list. In the second line, there is the general case in which the list consists of at least one element: x: xs. x<\/span> is the first element in the list, and xs<\/span> is the reminder by convention.<\/p>\n
The quicksort algorithm strategy can be directly applied to Haskell.<\/p>\n