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'''Software analytics''' is the [[analytics]] specific to the ___domain of [[software system]]s taking into account [[source code]], static and dynamic characteristics (e.g., [[software metric]]s) as well as related processes of their [[software development|development]] and [[software evolution|evolution]]. It aims at describing, monitoring, predicting, and improving the efficiency and effectiveness of [[software engineering]] throughout the [[software lifecycle]], in particular during [[software development]] and [[software maintenance]]. The data collection is typically done by mining [[software repository|software repositories]], but can also be achieved by collecting user actions or production data.
== Definitions ==
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Core data sources include [[source code]], "check-ins, work items, bug reports and test executions [...] recorded in software repositories such as CVS, Subversion, GIT, and Bugzilla."<ref>Harald Gall, Tim Menzies, [[Laurie Williams (software engineer)|Laurie Williams]], and Thomas Zimmerman. "Software Development Analytics". Dagstuhl Reports, Vol. 4, Issue 6, pp. 64-83.</ref> [[telemetry | Telemetry data]] as well as execution traces or logs can also be taken into account.
Automated analysis, massive data, and systematic reasoning support decision-making at almost all levels. In general, key technologies employed by software analytics include analytical technologies such as [[machine learning]], [[data mining]], [[statistics]], [[pattern recognition]], [[information visualization]] as well as large-scale data computing & processing. For example, software analytics tools allow users to map derived analysis results by means of [[software map]]s, which support interactively exploring system artifacts and correlated software metrics. There are also software analytics tools using analytical technologies on top of [[software quality]] models in [[agile software development]] companies, which support assessing software qualities (e.g., reliability), and deriving actions for their improvement.<ref>{{Cite journal|
== History ==
{{Expert needed|Software|reason=it misrepresents the history of software analytics, strengthening a single researcher group that claims to have coined the expression software analytics|date=August 2017}}
In
The term has since become well known in the [[software engineering]] research community after a series of tutorials and talks on software analytics were given by In November 2010, Software Development Analytics (Software Analytics with a focus on Software Development) was proposed by Thomas Zimmermann and his colleagues at the Empirical Software Engineering Group (ESE) at Microsoft Research Redmond in their FoSER 2010 paper.<ref name="FoSER" /> A goldfish bowl panel on software development analytics was organized by Zimmermann and [[Tim Menzies]] from West Virginia University at the International Conference on Software Engineering, Software Engineering in Practice Track.<ref name="Goldfish" />
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