Other information sources, such as coding activities, are also included to create a comprehensive impression of the quality and development progress of a software system.
Through the early-warning approach of KPI driven code analysis, every newly introduced level of complexity is discovered in good time and its impact can thus be minimized.
In this way, the quality of software delivered by each individual developer can be determined and any problems in employee qualification, direction and motivation can be identified early and appropriate measures introduced to resolve them.
For this purpose, KPI driven code analysis borrows methods taken from data mining and business intelligence, otherwise used in accounting and customer analytics.
The data sources include, in particular: Due to the many influencing factors which feed into the analysis data model, methods of optimizing the source code can be identified as well as requirements for action in the areas of employee qualification, employee direction and development processes: Finally the analysis data model of the KPI driven code analysis provides IT project managers, at a very early stage, with a comprehensive overview of the status of the software produced, the skills and effort of the employees as well as the maturity of the software development process.