Optimum control limits for employing statistical process control in software process

There is increasing interest in using control charts for monitoring and improving software processes, particularly quality control processes like reviews and testing. In a control chart, control limits are established for attributes and, if any point falls outside the limits, it is assumed to be due to special causes that need to be identified and eliminated. If the control limits are too tight, they may raise too many "false alarms" and, if they are too wide, they may miss special situations. Optimal control limits will try to minimize the cost of these errors. In this paper, we develop a cost model for employing control charts for software processes using optimum control limits which can be determined. Our applications of the model suggest that, for quality control processes like inspection, optimum control limits may be tighter than those commonly used in manufacturing. We have also implemented this model as a Web service that can be used for determining optimum control limits.