R Programming Training in Tiruchirappalli

Advantages R Programming

• Operational Overview The development, release and maintenance of R is, broadly, a collaborative process involving the R Development Core Team (hereafter referred to as R Core). Members of R Core represent multiple statistical disciplines and are based at academic, not-for-profit and industry-affiliated institutions on multiple continents.
• Most communications amongst the members of R Core take place electronically via e-mail and similar means.
• A non-public e-mail list (r-core) provides a common forum for discussions amongst the members of R Core.
• An archive of the list is available to facilitate R Core in documenting and reviewing these discussions, as they pertain to development decisions and related issues.
• R Core does meet, collectively and/or in smaller groups, with a level of frequency dictated by multiple factors, including taking advantage of regularly scheduled conferences where members of R Core may already be in attendance.
• Such conferences include those that are specific to statistical computing and R itself .
• These routine communications and meetings ensure that the collaborative efforts are appropriately coordinated and prioritized as ongoing development takes place.
• Reasonable software development and testing methodologies are employed by R Core in order to maximize the accuracy, reliability and consistency of R’s performance. While some aspects of R’s development are handled collaboratively, others are handled by members of the team with specific interests and expertise in focused areas.
• Importantly, as R is released under the terms of the GPL, all of the source code underlying R, whether it be in R, C or FORTRAN, is available for peer review by all members of the R user community.
• Thus, all of the functionality embodied within R is subject to continuous critique and improvement relative to its accuracy, reliability and consistency.
• The size of the R user community (difficult to define precisely, because there are no sales transactions, but conservatively estimated as being in the tens of thousands, with some independent estimates in the hundreds of thousands), provides for extensive review of source code and testing in “real world” settings outside the confines of the formalized testing performed by R Core.
• This is a key distinction, related to product quality, between R and similar software that is only available to end users in a binary, executable format.
• In conjunction with detailed documentation and references provided to end users, the size of the R user community, all having full access to the source code, enables a superior ability to anticipate and verify R’s performance and the results produced by R. Additional documentation regarding the activities of R Core as they pertain to development, goals and related activities, including coding guidelines, are available for review:
•  R Developer Page 
•  R Internals – A Guide to the Internal Structures of R and Coding Standards for the R Core Team 
• Source Code Management All of R’s source code is managed in a source code version control repository based on Subversion.
• The R Subversion Repository is access controlled, such that only members of R Core have write access to the R: Software Development Life Cycle 8 March 25, 2018 source code tree. Various security, access control and archival procedures are in place to provide reasonable protection and to maintain the integrity of the hosting server and the source code management system.
• Separate source code branches for version control are maintained by R Core.
• The current Release Branch and the ongoing Development Version are kept in separate branches to facilitate non-conflicting source code management.
• The Release Branch is designed for bug fixes and allows only minor feature enhancements.
• Major features are introduced in the Development Version, from which a new Release Branch is made prior to the next x.y.0 release.
• Daily logs of code changes are maintained within the Subversion repository and reflect all aspects of code changes made by R Core
•  In addition, a “NEWS” file is actively maintained by R Core to make it easier for users to track changes made to past, present and future versions of R.
•  This file is also included in all source code and binary executable versions of R to enable end users to review and gain insight into the ongoing changes to R via the news() function. The typical format of the NEWS file contains detailed,
• version-specific information on: • Significant User-Visible Changes • New Features • Graphics Devices • Installation • Package Installation • Utilities • Deprecated and Defunct • C-Level Facilities • Bug Fixes The entire list (and any additions) may or may not be present for each R version as appropriate.
• Each Released Version of R is actively supported by R Core with respect to bug reporting, fixes and patches. Patched versions are made available, generally as source code only, to end users to facilitate their installation of these.
• Binary executable installation files for the patched Release Versions are made available at the discretion of the individual maintainers of the platform specific versions.
• Source code tarballs of the daily incremental patched versions of each current R release are made available to the community via an FTP server for download to enable R users to update their systems between formal releases as their local needs may dictate.
• In addition, users with Subversion clients can download the latest copy of the source code tree at any time, via a direct connection to the Subversion server. As each version of R is released, there are a variety of support resources that are made available to the community of end users.
• Extensive documentation is provided by R Core and is available both within the source code and binary executable versions of R as well as online in HTML and PDF formats .
• Function-specific help is also available within R including, where appropriate, extensive references to algorithms and methods to facilitate the user’s comprehension of R’s functionality and expected behavior