KPI driven code analysis (KPI = Key Performance Indicator) is a method of analyzing software source code and source code related IT systems to gain insight into business critical aspects of the development of a software system such as team-performance, time-to-market, risk-management, failure-prediction and much more.
The KPI driven code analysis - developed at the Hasso Plattner Institute - is a static program analysis of source code for the purpose of improving software quality. However, the KPI driven code analysis does not only analyze the source code. 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.
KPI driven code analysis is a fully automated process which thus enables team activities and modifications to the overall source code of a software system to be monitored in real time. In this way, negative trends become evident as soon as they arise. This “early warning system” thus offers a powerful instrument for reducing costs and increasing development speed. 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. Instead of wasting valuable time trying to reduce legacy complexities, developers can use their time for new functionality, helping the team increase productivity.
The “human factor” is included in the KPI driven code analysis which means that it also looks at which code was registered by which developer and when. 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.
In order to determine the key performance indicators (KPIs) – figures which are crucial to the productivity and success of software development projects – numerous data sources related to the software code are read out. For this purpose, KPI driven code analysis borrows methods taken from data mining and business intelligence, otherwise used in accounting and customer analytics. The KPI driven code analysis extracts data from the following sources and consolidates them in an analysis data model. On this data model, the values of the key performance indicators are calculated. 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.
One method of representation of the analysis data would be so-called software maps.
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This article discusses a set of tactics useful in software testing. It is intended as a comprehensive list of tactical approaches to software quality assurance and general application of the test method.