Optimum control limits for employing statistical process control in software process

There is an increased 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 some attributes and, if any point falls outside the limits, it is assumed to be due to some 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 some 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 to software process using which optimum control limits can be determined. Our applications of the model suggest that, for quality control processes like the inspection process, the optimum control limits may be tighter than what is commonly used in manufacturing. We have also implemented this model as a web-service that can be used for determining optimum control limits.