A novel approach to software quality risk management

Abstract

SUMMARYSoftware quality is very important in today's competitive business environment. It is a critical constraint on software projects. Software organizations’ major objectives are delivering products on time and achieving quality goals. Quality is directly dependent on software processes, which are inherently variable and uncertain, involving substantial risk. Managing quality risk is an important challenge. The conventional approach to quality risk management for ongoing software processes has two major deficiencies: static analytic models are used, and structured methodologies to enhance processes and improve quality are not systematically applied. This new practical method uses Six Sigma and Monte Carlo Simulation for ongoing quality risk management. DMAIC (Define, Measure, Analyse, Improve, Control) is systematically applied as a tactical framework to enhance the process and improve quality. Simulation predicts quality (reliability) at the expected process end and identifies and quantifies risk. DMAIC is a verified structured methodology for systematic process and quality improvements. Monte Carlo Simulation is superior to conventional risk models. These synergetic enhancements eliminate observed deficiencies. The method has been successfully proven and applied practically on real in‐house projects. Substantial savings, quality and customer satisfaction have been achieved. An application on an internal project and obtained results are presented. The method is simplistically elaborated on a published third‐party project answering key research questions from practical perspectives. This CMMI® compliant method offers important benefits including savings, quality and customer satisfaction. Copyright © 2013 John Wiley & Sons, Ltd.