01974cam a22003255a 45000010009000000050017000090080041000260200018000670400040000850820021001252450114001462600052002603000036003125000024003485040041003725060046004135200695004595900078011545900047012326500031012796500041013106510010013516530024013617000030013857000027014157000040014429420008014829990017014909520141015071268180320161018125126.0151128t2015    maua   frb    001 0 eng d  z9780124115194  aCtWfDGIbengepncCtWfDGIdEG-ScBUE04a006.312222bART04aThe art and science of analyzing software data /c[edited by] Christian Bird, Tim Menzies, Thomas Zimmermann.  aWaltham :bMorgan Kaufmann / Elsevier,cc.2015.  axxiii, 660 p. :bill. ;c24 cm.  aIndex : p. 649-660.  aIncludes bibliographical references.  aAccess restricted by licensing agreement.  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. --  aFirst time users must register for a free personal username and password.  aAccess is available to the Yale community. 7aData mining.2BUEsh927695 7aQuantitative research.2BUEsh912353  2BUEsh  bCOMSCIcOctober20161 aBird, Christian,eeditor.1 aMenzies, Tim,eeditor.1 aZimmermann, Thomas,d1961-eeditor.  2ddc  c22682d22654  00102ddc40708BaccahaMAINbMAINcLOWd2016-10-18ePurchaseg595.00h9128l0o006.312 ARTp000034323r2025-07-15 00:00:00v743.75yBB