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{{Expert-subject needed|Softwaresoftware|reason=it appears to be written by a non-native English speaker, it provides unusual minor examples of software analytics platforms without mentioning major ones, and it misrepresentsmisrepresent the history of software analytics|date=December 2014}}

'''Software Analyticsanalytics''' refersis tothe [[analytics]] specific to the ___domain of [[software system]]s taking into account [[source code]], static and relateddynamic characteristics (e.g., [[software development processmetric]]es.s) Itas aimswell atas describing,related predicting,processes andof improvingtheir [[software development|development]], and [[software maintenanceevolution|maintenanceevolution]], and management of complex software systems. MethodsIt andaims techniquesat ofdescribing, software analytics typically rely on gatheringmonitoring, analyzingpredicting, and visualizingimproving informationthe foundefficiency inand theeffectiveness manifoldof data[[software sourcesengineering]] inthroughout the scope of [[software systemslifecycle]], andin theirparticular during [[software development]] processes---and [[software analyticsmaintenance]]. "turnsThe itdata intocollection actionableis insighttypically todone informby bettermining decisions related to[[software repository|software".<ref>Harald Gallrepositories]], Timbut Menzies,can Lauriealso Williams,be andachieved Thomasby Zimmerman.collecting "Softwareuser Developmentactions Analytics".or Dagstuhlproduction Reports, Vol. 4, Issue 6, pp. 64-83data.</ref>

== Definitions ==

Software analytics represents a base component of [[software diagnosis]] that generally aims at generating findings, conclusions, and evaluations about software systems and their implementation, composition, behavior, and evolution. Software analytics frequently uses and combines approaches and techniques from statistics, prediction analysis, data mining, and scientific visualization. For example, software analytics can map data by means of [[software map]]s that allow for interactive exploration.

* "Software analytics aims to obtain insightful and actionable information from software artifacts that help practitioners accomplish tasks related to software development, systems, and users."<ref name="IEEESoftware-2013" /> --- centers on analytics applied to artifacts a software system is composed of.

Data under exploration and analysis by Software Analytics exists in software lifecycle, including [[source code]], software requirement specifications, bug reports, test cases, execution traces/logs, and real-world user feedback, etc. Data plays a critical role in modern software development, because hidden in the data is the information and insight about the quality of software and services, the experience that software users receive, as well as the dynamics of software development.

* "Software analytics is analytics on software data for managers and software engineers with the aim of empowering software development individuals and teams to gain and share insight form their data to make better decisions."<ref name="ICSESEIP12InfoNeeds"/> --- strengthens the core objectives for methods and techniques of software analytics, focusing on both software artifacts and activities of involved developers and teams.

* "Software analytics (SA) represents a branch of [[big data]] analytics. SA is concerned with the analysis of all software artifacts, not only source code. [...] These tiers vary from the higher level of the management board and setting the enterprise vision and portfolio management, going through project management planning and implementation by software developers."<ref name="BIGDSE2015" /> --- reflects the broad scope including various stakeholders.

== HistoryAims ==

Insightful information obtained by Software Analytics is information that conveys meaningful and useful understanding or knowledge towards performing the target task. Typically insightful information cannot be easily obtained by direct investigation on the raw data without the aid of analytic technologies.

Software analytics aims at supporting decisions and generating insights, i.e., findings, conclusions, and evaluations about software systems and their implementation, composition, behavior, quality, evolution as well as about the activities of various stakeholders of these processes.

* Insightful information obtained by Softwaresoftware Analytics is information thatanalytics conveys meaningful and useful understanding or knowledge towards performing the target tasktasks. Typically, insightful informationit cannot be easily obtained by direct investigationexamining onraw the rawbig data without the aid of analyticanalytics technologiesmethods and techniques.

* Actionable information obtained by software analytics steers or prescribes solutions that stakeholders in software engineering processes may take (e.g., software practitioners, development leaders, or C-level management).

== Approach ==

Actionable information obtained by Software Analytics is information upon which software practitioners can come up with concrete solutions (better than existing solutions if any) towards completing the target task.

Methods, techniques, and tools of software analytics typically rely on gathering, measuring, analyzing, and visualizing information found in the manifold data sources stored in software development environments and ecosystems. Software systems are well suited for applying analytics because, on the one hand, mostly formalized and precise data is available and, on the other hand, software systems are extremely difficult to manage ---in a nutshell: "software projects are highly measurable, but often unpredictable."<ref name="ICSESEIP12InfoNeeds"/>

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.

Software Analytics focuses on trinity of software systems, software users, and software development process:

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|last1=Martínez-Fernández|first1=Silverio|last2=Vollmer|first2=Anna Maria|last3=Jedlitschka|first3=Andreas|last4=Franch|first4=Xavier|last5=Lopez|first5=Lidia|last6=Ram|first6=Prabhat|last7=Rodriguez|first7=Pilar|last8=Aaramaa|first8=Sanja|last9=Bagnato|first9=Alessandra|date=2019|title=Continuously assessing and improving software quality with software analytics tools: a case study|journal=IEEE Access|volume=7|pages=68219–68239|doi=10.1109/ACCESS.2019.2917403|issn=2169-3536|url=https://upcommons.upc.edu/bitstream/2117/133374/1/FINAL-Access-Paper-preprint.pdf|doi-access=free|bibcode=2019IEEEA...768219M }}</ref>

'''Software Systems'''. Depending on scale and complexity, the spectrum of software systems can span from operating systems for devices to large networked systems that consist of thousands of servers. System quality such as reliability, performance and security, etc., is the key to success of modern software systems. As the system scale and complexity greatly increase, larger amount of data, e.g., run-time traces and logs, is generated; and data becomes a critical means to monitor, analyze, understand and improve system quality.

== History ==

'''Software Users'''. Users are (almost) always right because ultimately they will use the software and services in various ways. Therefore, it is important to continuously provide the best experience to users. Usage data collected from the real world reveals how users interact with software and services. The data is incredibly valuable for software practitioners to better understand their customers and gain insights on how to improve user experience accordingly.

{{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}}

'''Software Development Process'''.<ref name="ICSESEIP12InfoNeeds"/><ref name="ICSENIER11" /> Software development has evolved from its traditional form to exhibiting different characteristics. The process is more agile and engineers are more collaborative than that in the past. Analytics on software development data provides a powerful mechanism that software practitioners can leverage to achieve higher development productivity.

In 2009, the term "software analytics" was used in a paper by [[Dongmei Zhang]], Shi Han, Yingnong Dang, Jian-Guang Lou, and Haidong Zhang in part by the Software Analytics Group (SA) at [[Microsoft Research]] Asia (MSRA).<ref>{{Cite web |last=Brannon |first=Brian G. |date=23 June 2013 |title=Software Analytics in Practice |url=https://www.microsoft.com/en-us/research/wp-content/uploads/2016/07/ieeesoft13-softanalytics.pdf |access-date=31 December 2024 |website=microsoft.com}}</ref>

In general, the primary technologies employed by Software Analytics include analytical technologies such as [[machine learning]], [[data mining]] and [[pattern recognition]], [[information visualization]], as well as large-scale data computing & processing.

In May 2009, Software Analytics was first coined and proposed when Dr. Dongmei Zhang founded [http://research.microsoft.com/en-us/groups/sa/ the Software Analytics Group (SA) at Microsoft Research Asia (MSRA)]. 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 Dr.the DongmeiSoftware ZhangAnalytics and her colleaguesGroup, in collaboration with Professor [http://people.engr.ncsu.edu/txie/ Tao Xie] from [[North Carolina State University]], at software engineering conferences including a tutorial at the IEEE/ACM [[International Conference on Automated Software Engineering]] (ASE 2011),<ref name="ASE2011" /> a talk at the International Workshop on Machine Learning Technologies in Software Engineering (MALETS 2011),<ref name="MALETS" /> a tutorial and a keynote talk given by Dr. Dongmei Zhang at the IEEE-CS Conference on Software Engineering Education and Training ([http://conferences.computer.org/cseet/ CSEE&T 2012]),<ref name="CSEETKeynote" /><ref name="CSEETTutorial" /> a tutorial at the International Conference on Software Engineering ([http://www.ifi.uzh.ch/icse2012/ ICSE 2012]) - Software Engineering in Practice Track,<ref name="ICSETutorial" /> and a keynote talk given by Dr. Dongmei Zhang at the Working Conference on Mining Software Repositories ([http://2012.msrconf.org/ MSR 2012]).<ref name="MSRKeynote" />

== History ==

In May 2009, Software Analytics was first coined and proposed when Dr. Dongmei Zhang founded [http://research.microsoft.com/en-us/groups/sa/ the Software Analytics Group (SA) at Microsoft Research Asia (MSRA)]. The term has become well known in the [[software engineering]] research community after a series of tutorials and talks on software analytics were given by Dr. Dongmei Zhang and her colleagues, in collaboration with Professor [http://people.engr.ncsu.edu/txie/ Tao Xie] from North Carolina State University, at software engineering conferences including a tutorial at the IEEE/ACM International Conference on Automated Software Engineering (ASE 2011),<ref name="ASE2011" /> a talk at the International Workshop on Machine Learning Technologies in Software Engineering (MALETS 2011),<ref name="MALETS" /> a tutorial and a keynote talk given by Dr. Dongmei Zhang at the IEEE-CS Conference on Software Engineering Education and Training ([http://conferences.computer.org/cseet/ CSEE&T 2012]),<ref name="CSEETKeynote" /><ref name="CSEETTutorial" /> a tutorial at the International Conference on Software Engineering ([http://www.ifi.uzh.ch/icse2012/ ICSE 2012]) - Software Engineering in Practice Track,<ref name="ICSETutorial" /> and a keynote talk given by Dr. Dongmei Zhang at the Working Conference on Mining Software Repositories ([http://2012.msrconf.org/ MSR 2012]).<ref name="MSRKeynote" />

In November 2010, Software Development Analytics (Software Analytics with a focus on Software Development) was proposed by [http://research.microsoft.com/en-us/people/tzimmer/ Thomas Zimmermann] and his colleagues at [http://research.microsoft.com/en-us/groups/ese/ 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 [http://research.microsoft.com/en-us/people/tzimmer/ Thomas Zimmermann] and Professor [http://menzies.us/ [Tim Menzies]] from West Virginia University at the International Conference on Software Engineering ([http://www.ifi.uzh.ch/icse2012/ ICSE 2012]), Software Engineering in Practice trackTrack.<ref name="Goldfish" />

==Software Analytics Providers==

* [[ CAST Software ]]

* [[IBM Cognos Business Intelligence]]

* [[Kiuwan]]

* Microsoft Azure Application Insights <ref>{{cite web|url=https://azure.microsoft.com/en-us/services/application-insights/|title=Microsoft Azure Application Insights - Portal|date=June 2016|website = Microsoft Azure|publisher = Microsoft }}</ref>

* [[Nalpeiron|Nalpeiron Software Analytics]]

* [[New Relic]]

* [[Tableau Software]]

* Trackerbird Software Analytics <ref>{{cite web|url=http://www.trackerbird.com/ |title=Trackerbird Software Analytics|date=July 2016|website = Trackerbird|publisher = Trackerbird}}</ref>

==See also==

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refs=

<ref name="FoSER">Raymond P. L. Buse and Thomas Zimmermann. "Analytics for Software Development." In Proceedings of the Workshop on Future of Software Engineering Research (FoSER 2010), Santa Fe, NM, USA, November 2010, pp. 77-80.</ref>[http://research.microsoft.com/apps/pubs/default.aspx?id=136301 PDF]

refs=

<ref name="ICSENIER11">Kenneth Hullett, Nachiappan Nagappan, Eric Schuh, and John Hopson, "Data Analytics for Game Development (NIER Track)". In Proceedings of the International Conference on Software Engineering, May 2011, pp. 940-943.</ref> [http://dl.acm.org/citation.cfm?id=1985952 PDF]

<ref name="MALETS">Dongmei Zhang, Yingnong Dang, Jian-Guang Lou, Shi Han, Haidong Zhang, and Tao Xie. "Software Analytics as a Learning Case in Practice: Approaches and Experiences". In Proceedings of International Workshop on Machine Learning Technologies in Software Engineering (MALETS 2011), Lawrence, Kansas, November 2011. [http://people.engr.ncsu.edu/txie/publications/malets11-analytics.pdf PDF][https://sites.google.com/site/xsoftanalytics/malets11-msrasa.pdf?attredirects=0 Slides]</ref>

<ref name="BIGDSE2015">T. M. Abdellatif, L. F. Capretz, D. Ho. "Software Analytics to Software Practice: A Systematic Literature Review". 1. Int'l Workshop on Big Data Engineering, 2015, pp. 30-36.</ref>

<ref name="ASE2011">Dongmei Zhang and Tao Xie. "xSA: eXtreme Software Analytics - Marriage of eXtreme Computing and Software Analytics." In Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011), Tutorial, Lawrence, Kansas, November 2011.</ref>

<ref name="IEEESoftware-2013">D. Zhang, S. han, Y. Dan, J.-G. Lou, H Zhang: "Software Analytics in Practice". IEEE Software, Sept./Oct. 2013, pp. 30-35.</ref>

<ref name="CSEETKeynote">Dongmei Zhang. "Software Analytics in Practice and Its Implications for Education and Training." Keynote. In Proceedings of the 24th IEEE-CS Conference on Software Engineering Education and Training (CSEE&T 2012), Tutorial, Nanjing, China, April 2012.</ref>

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* [http://research.microsoft.com/en-us/groups/ese/ Microsoft Research Redmond Empirical Software Engineering Group (ESE)]

* [http://conferences.computer.org/cseet/2012/CSEET_2012/Dongmei.html Software Analytics in Practice and Its Implications for Education and Training, Keynote by Dongmei Zhang at the 24th IEEE-CS Conference on Software Engineering Education and Training (CSEE&T 2012)]

* [http://research.microsoft.com/en-us/groups/sa/softwareanalyticsinpractice_approachesandexperiences_msr2012.pdf Software Analytics in Practice – Approaches and Experiences, Keynote slides by Dongmei Zhang at the 9th Working Conference on Mining Software Repositories (MSR 2012)]

* [http://research.microsoft.com/en-us/groups/sa/softwareanalyticsinpractice_minitutorial_icse2012.pdf Software Analytics in Practice, Mini-tutorial slides by Dongmei Zhang and Tao Xie at the 34th International Conference on Software Engineering (ICSE 2012)]

* [https://sites.google.com/site/xsoftanalytics/ Software Analytics Portal]

* [http://pinterest.com/tomzimmermann/software-analytics/ Software Analytics Pinterest]

* [https://azure.microsoft.com/en-us/services/application-insights/ Microsoft Azure - Application Insights in Azure]

* [http://for-managers.com/people-analytics-big-data-workplace/ People Analytics – Applying Big Data to Affect Big Changes in the Workplace]

[[Category:Software maintenance]]

[[Category:Types of analytics]]