000 03797nam a22005535i 4500
001 978-3-319-25964-2
003 DE-He213
005 20220801215002.0
007 cr nn 008mamaa
008 160114s2016 sz | s |||| 0|eng d
020 _a9783319259642
_9978-3-319-25964-2
024 7 _a10.1007/978-3-319-25964-2
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aComputational Intelligence and Quantitative Software Engineering
_h[electronic resource] /
_cedited by Witold Pedrycz, Giancarlo Succi, Alberto Sillitti.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aIX, 207 p. 41 illus., 15 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v617
520 _aIn a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and opens up a novel and promising avenue of a comprehensive analysis and advanced design of software artifacts. It shows how the paradigm and the best practices of Computational Intelligence can be creatively explored to carry out comprehensive software requirement analysis, support design, testing, and maintenance. Software Engineering is an intensive knowledge-based endeavor of inherent human-centric nature, which profoundly relies on acquiring semiformal knowledge and then processing it to produce a running system. The knowledge spans a wide variety of artifacts, from requirements, captured in the interaction with customers, to design practices, testing, and code management strategies, which rely on the knowledge of the running system. This volume consists of contributions written by widely acknowledged experts in the field who reveal how the Software Engineering benefits from the key foundations and synergistically existing technologies of Computational Intelligence being focused on knowledge representation, learning mechanisms, and population-based global optimization strategies. This book can serve as a highly useful reference material for researchers, software engineers and graduate students and senior undergraduate students in Software Engineering and its sub-disciplines, Internet engineering, Computational Intelligence, management, operations research, and knowledge-based systems.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 0 _aSoftware engineering.
_94138
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aSoftware Engineering.
_94138
700 1 _aPedrycz, Witold.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_941634
700 1 _aSucci, Giancarlo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_941635
700 1 _aSillitti, Alberto.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_941636
710 2 _aSpringerLink (Online service)
_941637
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319259628
776 0 8 _iPrinted edition:
_z9783319259635
776 0 8 _iPrinted edition:
_z9783319798660
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v617
_941638
856 4 0 _uhttps://doi.org/10.1007/978-3-319-25964-2
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c76980
_d76980