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008			200107s2020 gw a o |||| 0|eng d
020			_a9783030380069
024	7		_a10.1007/978-3-030-38006-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.758 _b2020 EB
100	1		_aSatapathy, Suresh Chandra _eautor _998975
245	1	0	_aAutomated Software Engineering : _bA Deep Learning-Based Approach _cby Suresh Chandra Satapathy, Ajay Kumar Jena, Jagannath Singh, Saurabh Bilgaiyan.
250			_a1st ed. 2020.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2020.
300			_a1 recurso en línea (XI, 118 páginas)
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aLearning and Analytics in Intelligent Systems _x2662-3447 _v8
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aChapter 1: Selection of Significant Metrics for Improving the Performance of Change-Proneness Modules -- Chapter 2: Effort Estimation of Web based Applications using ERD, use Case Point Method and Machine Learning -- Chapter 3: Usage of Machine Learning in Software Testing -- Chapter 4: Test Scenarios Generation using Combined Object-Oriented Models -- Chapter 5: A Novel Approach of Software Fault Prediction using Deep Learning Technique -- Chapter 6: Feature-Based Semi-Supervised Learning to Detect Malware from Android.
520	3		_aThis book discusses various open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation. Many traditional techniques are available for addressing these problems. But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software's complexity. Hence, many previously used methods are proving insufficient to solve the problems now arising in software development. The book highlights a number of unique problems and effective solutions that reflect the state-of-the-art in software engineering. Deep learning is the latest computing technique, and is now gaining popularity in various fields of software engineering. This book explores new trends and experiments that have yielded promising solutions to current challenges in software engineering. As such, it offers a valuable reference guide for a broad audience including systems analysts, software engineers, researchers, graduate students and professors engaged in teaching software engineering.
988			_aPrimersemestre_2020_Robotics
650		7	_2embne _aIngeniería del software _9152630
700	1		_aJena, Ajay Kumar _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aSingh, Jagannath _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aBilgaiyan, Saurabh _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030380052
776	0	8	_iPrinted edition: _z9783030380076
776	0	8	_iPrinted edition: _z9783030380083
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-38006-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2020 _dz _ek _zSI