Drivers for Customer Perceived Software Quality

Predicting software quality as perceived by a customer may allow an organization to adjust deployment to meet the quality expectations of its customers, to allocate the appropriate amount of maintenance resources, and to help direct quality improvement efforts to maximize return on investment. However, customer perceived quality may be affected not simply by the software content and the development process, but also by a number of other factors including deployment issues, amount of usage, software platforms and hardware configurations. We predict customer perceived quality as measured by various service interactions, including software defect reports, request for assistance, and field technician dispatches using the afore mentioned and other factors for a large software system. We employ the non-intrusive data gathering technique of using existing data captured in automated project monitoring and tracking systems as well as customer support and tracking systems. We find that the effect of deployment schedule, hardware platform, and software configurations can increase the probability of observing failures more that 20 times, Furthermore, we found that the factors affected all quality measures in similar fashion. Our theoretical model could be applied at other organizations, and we suggest methods to independently validate and replicate our results.