Tracking stability of software evolution using statistical process control limit

The way software systems evolve is a process that needs strict and careful tracking, monitoring and evaluation; it is therefore pertinent that software evolutionary cyclical states are tracked, monitored and analyzed to ensure that the process does not get out of control, guaranteeing the stability of the software system as it evolves. This research utilized a statistical process control approach to monitor, track and evaluate whether the change process is in control or not, and discover situations where the process is in or out of kilter. Statistical process control provides the means through which a process stability can be analyzed, controlled and managed. Some of the contributions of this research include the introduction of SCAR metric that allows the collapsing of data about software module maintenance activities over the period in which the software system evolves; and a methodology that helps monitor and track software evolution process guaranteeing that it does not move towards chaos, degradation and decay.