Development of Learning Application for Visualisation of Events and Facilities of ATLAS Detector
Collaborative partners:  University of Glasgow,   University of Arizona

A number of static code analyzers are now available to systematically flag suspicious code in a large software project. These tools, like Coverity, CppCheck, and Lizard, look for instances of uninitialized variables that could cause run time problems, dead code and other indications of implementation mistakes, copy-paste errors, overly-complex methods that will harm future maintainability, and similar problems. The tools provide regularly-updated reports on the quality of the ATLAS offline software, including lists of high-, medium-, and low-priority issues. The Georgian Team will help to improve the quality of the ATLAS code by providing patches for these issues. Progress will be visible in the “league tables” already provided as part of the output of the tools, which indicate both as a function of project and as a function of time the rate and number of issues flagged by the tools.