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Abstractespite the significant evolution within the software industry, software quality remains a pertinent problem to many organisations today. This is because interactions between software project parameters in software development environment are complex and dynamic. Both management and developers have problems monitoring the fluctuations in quality that occur within the development process. This paper provides an insight on quality fluctuations that occur in a software project, using a quality index. The research focuses not only on changes on software project parameters that occur at the end but also throughout the software development process through dynamic modelling. The findings proved the ratio of 75-25 experienced to inexperienced staffs percentage to be the most practical combination. Likewise, the right balance of schedule pressure is determined and recommended so that it contributes to increasing the productivity during software development.Keywords-Software Quality, System Dynamics, Modelling, Software Projects, Quality Index I. INTRODUCTIONSoftware is among the most widely used product in human history; and it also has one of the highest failure rates due to the lack of quality in the end-products. Literature shows that software projects frequently suffered from qualityrelated problems in recent past years (Austin, 2001;Charette, 2005;Devedzic, 2001;Land et al., 2005;Lindstrom and Jeffries, 2004;Meso and Jain, 2006;Molokken-Ostvold and Jorgensen, 2005;Rose, 2005;Wiegers, 2009). It is therefore of crucial importance to understand the element of quality when developing software. Software quality can no longer be considered insignificant or left unmeasured since there is too much financial and essential business value at stake.The aim of this paper is to formulate a dynamic model that will improve software quality management. For this purpose, surveys will be carried out in software development companies, and causal loop diagrams for quality models will be developed. Subsequently, a dynamic model will be formulated from the cause and effect diagrams using System Dynamics. The results of the model shall be calibrated, verified and validated with original data from 3 web-based software projects. Furthermore, the margin of error will be calculated to show the precision of the simulated output.

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