000			01821cam a22003135a 4500
001			12681803
005			20161018125126.0
008			151128t2015 maua frb 001 0 eng d
020			_z9780124115194
040			_aCtWfDGI _beng _epn _cCtWfDGI _dEG-ScBUE
082	0	4	_a006.312 _222 _bART
245	0	4	_aThe art and science of analyzing software data / _c[edited by] Christian Bird, Tim Menzies, Thomas Zimmermann.
260			_aWaltham : _bMorgan Kaufmann / Elsevier, _cc.2015.
300			_axxiii, 660 p. : _bill. ; _c24 cm.
500			_aIndex : p. 649-660.
504			_aIncludes bibliographical references.
506			_aAccess restricted by licensing agreement.
520			_aThis book provides valuable information on analysis techniques often used to derive insight from software data. It shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. Topics include: analysis of security data; code reviews; app stores; log files; user telemetry; co-change, text, topic and concept analyses; release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. --
590			_aFirst time users must register for a free personal username and password.
590			_aAccess is available to the Yale community.
650		7	_aData mining. _2BUEsh _927695
650		7	_aQuantitative research. _2BUEsh _912353
651			_2BUEsh
653			_bCOMSCI _cOctober2016
700	1		_aBird, Christian, _eeditor.
700	1		_aMenzies, Tim, _eeditor.
700	1		_aZimmermann, Thomas, _d1961- _eeditor.
942			_2ddc
999			_c22682 _d22654