000			03442nam a22005175i 4500
001			978-3-319-25964-2
003			DE-He213
005			20200421111706.0
007			cr nn 008mamaa
008			160114s2016 gw | 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	_aCOM004000 _2bisacsh
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., 26 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, _x1860-949X ; _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	_aEngineering.
650		0	_aSoftware engineering.
650		0	_aArtificial intelligence.
650		0	_aComputational intelligence.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aSoftware Engineering.
700	1		_aPedrycz, Witold. _eeditor.
700	1		_aSucci, Giancarlo. _eeditor.
700	1		_aSillitti, Alberto. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319259628
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v617
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-25964-2
912			_aZDB-2-ENG
942			_cEBK
999			_c55259 _d55259