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020   $a8871920511
040   $aBibl. Dip.le Aggr. Ingegneria Innovazione - Sez. IngegneriaInnovazione$beng
082 0 $a005.1
100 1 $aForni, Andrea$0308029
245 10$aObject-Oriented: Metodologie, strumenti, applicazioni /$cA. Forni
260   $aMilano :$bAddison-Wesley Masson,$c1992
300   $a221 p. :$bill. ;$c24 cm
650  0$aObject-oriented programming$xComputer science
650  0$aSoftware engineering
650  0$aApplication software
912   $a991004384330907536
996   $aObject-Oriented: Metodologie, strumenti, applicazioni$94386013
997   $aUNISALENTO

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010   $a3-319-77697-5
024 7 $a10.1007/978-3-319-77697-2
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035   $a(DE-He213)978-3-319-77697-2
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035   $a(MiAaPQ)EBC5578384
035   $a(Au-PeEL)EBL5578384
035   $a(OCoLC)1034555420
035   $a(PPN)226699188
035   $a(EXLCZ)994100000003359551
100   $a20180405d2018      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aRandom Numbers and Computers /$fby Ronald T. Kneusel
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (XVI, 260 p. 42 illus., 27 illus. in color.) 
311   $a3-319-77696-7 
327   $a1 Random and Pseudorandom Sequences -- 2 Generating Uniform Random Numbers -- 3 Generating Nonuniform Random Numbers -- 4 Testing Pseudorandom Generators -- 5 Parallel Random Number Generators -- 6 Cryptographically Secure Pseudorandom Number Generators -- 7 Other Random Sequences. .
330   $aThis book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples. Random Numbers and Computers is an essential introduction or refresher on pseudorandom numbers in computer science. The first comprehensive book on the topic, readers are provided with a practical introduction to the techniques of pseudorandom number generation, including how the algorithms work and how to test the output to decide if it is suitable for a particular purpose. Practical applications are demonstrated with hands-on presentation and descriptions that readers can apply directly to their own work. Examples are in C and Python and given with an emphasis on understanding the algorithms to the point of practical application. The examples are meant to be implemented, experimented with and improved/adapted by the reader. .
606   $aNumerical analysis
606   $aAlgorithms
606   $aData encryption (Computer science)
606   $aMathematical statistics
606   $aNumeric Computing$3https://scigraph.springernature.com/ontologies/product-market-codes/I1701X
606   $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021
606   $aAlgorithms$3https://scigraph.springernature.com/ontologies/product-market-codes/M14018
606   $aCryptology$3https://scigraph.springernature.com/ontologies/product-market-codes/I28020
606   $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036
615  0$aNumerical analysis.
615  0$aAlgorithms.
615  0$aData encryption (Computer science)
615  0$aMathematical statistics.
615 14$aNumeric Computing.
615 24$aAlgorithm Analysis and Problem Complexity.
615 24$aAlgorithms.
615 24$aCryptology.
615 24$aProbability and Statistics in Computer Science.
676   $a518
700   $aKneusel$b Ronald T$4aut$4http://id.loc.gov/vocabulary/relators/aut$0992662
801  0$bMiAaPQ
801  1$bMiAaPQ
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906   $aBOOK
912   $a9910299270203321
996   $aRandom Numbers and Computers$92273067
997   $aUNINA