A robust optimization model for software development costs considering time value of money

Abstract

Determining “software release time” and “testing stop time” is a significant challenge in software projects, as both greatly affect the software cost and reliability. To overcome the drawbacks of past research, this study presents a novel robust optimization approach considering the interval estimation of input parameters for a software reliability growth model. It aims to detect the optimal “software release time” and “testing stop time” to minimize software development costs in an uncertain environment. Additionally, it considers the time value of money for calculating model costs by considering the interest rate and inflation. Generally, this research is the first attempt to use a robust approach for optimizing the software development cost considering the time value of money. The paper investigates the model efficiency in practical situations through a case study and analyzes the effect of the discounted rate and parameters uncertainty on the development cost using a software reliability growth model. The results confirm the prominent role of uncertain parameters and the discounted rate value on software development cost. They also indicate that the proposed mathematical model is more consistent with the actual situation and flexible than the past models with deterministic parameters.