This paper is an application of multistage statistical process control for managing the software development process. The suggested methodology is a combination of process performance models and control charts. | Application of multistage process control methodology for software quality management Journal of Project Management 1 2016 55 66 Contents lists available at GrowingScience Journal of Project Management homepage Application of multistage process control methodology for software quality management Boby Johna R. S. Kadadevaramathb and I. A. Edinbaroughc a SQC amp OR Unit Indian Statistical Institute 8th Mile Mysore Road Bangalore Karnataka State India 560 059 b Department of Industrial Engineering amp Management Siddaganga Institute of Technology Tumkur Karnataka State India 572103 c Department of Manufacturing and Industrial Engineering University of Texas at Brownsville USA CHRONICLE ABSTRACT Article history As the need for software increased the number of software firms and the competition among Received October 1 2016 them also increased. The software companies in developing countries like India can no longer Received in revised format No- survive based on cost advantage alone. The firms need to deliver competitively priced quality vember 16 2016 software products on time. This can be achieved through quantitatively managing the different Accepted February 24 2017 Available online phases or sub processes in software development process. But quantitative management of a February 24 2017 process consisting of a set of interlinked sub processes or stages with the output of one sub Keywords process influencing that of subsequent stages and final output is not easy. The process perfor- Quantitative project management mance models developed for quantitative management of software development process often Defect density model the final outcome in terms of factors from various stages together or focuses only on Classification and regression tree quantitatively managing a particular sub process independently. In manufacturing and other en- Ridge regression gineering industries the processes with multiple sub process are monitored and controlled .
