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- Software_analytics abstract "Software Analytics is to utilize the data-driven approach to enable software practitioners to perform data exploration and analysis in order to obtain insightful and actionable information for completing various tasks around software systems, software users, and software development process.Software Analytics is a field within the area of Analytics, along with web analytics, fraud analytics, etc.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.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.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.Software Analytics focuses on trinity of software systems, software users, and software development process: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.Software Users. Users are (almost) always right because ultimately they will use for 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.Software Development Process. 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 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.".
- Software_analytics wikiPageExternalLink 2012.msrconf.org.
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- Software_analytics wikiPageExternalLink softwareanalyticsinpractice_approachesandexperiences_msr2012.pdf.
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- Software_analytics hasPhotoCollection Software_analytics.
- Software_analytics subject Category:Software_maintenance.
- Software_analytics subject Category:Mining_Software_Repositories.
- Software_analytics comment "Software Analytics is to utilize the data-driven approach to enable software practitioners to perform data exploration and analysis in order to obtain insightful and actionable information for completing various tasks around software systems, software users, and software development process.Software Analytics is a field within the area of Analytics, along with web analytics, fraud analytics, etc.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. ".
- Software_analytics label "Software analytics".
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