Function Point Analysis has become an important tool once again. In the era of low-code and no-code, faster development and faster time-to-market it serves as way to monitor and control the speed of your development teams. When the functional size is monitored over time and we divide this by the effort it took (in hours) a Productivity Analysis is possible. However, for the productivity analysis it is important to take the code complexity into account. After all, the accuracy of the Productivity Analysis heavily depends on the quality of the data used as input.
Improved quality of Effort Data
To calculate the effort BonCode uses the Enhancement Function Points metric. This metric has now been upgraded to also take into account the local complexity of functionality. This means that the Productivity Analysis has very detailed knowledge of the code complexity of certain functionality, therefore making it possible to calculate the total effort very accurately. For the end user this results in a high quality Productivity Analysis.
Identify Hotspots in time with a Productivity Analysis
Many projects have components that use up most of the time of your development teams. Usually these are a small number of components. We like to call them hotspots. These hotspots are often critical parts of the system that contain a lot of complex business logic. Hotspots also include components that require constant change due to requirements changes.
Hotspots consist of business-critical functionality and require a lot of time and effort to maintain. This makes them more prone to a loss of code and architecture quality. Monitoring hotspots creates awareness and mitigates risks.
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