Prototyping an algorithm for parameter tuning of Software cost estimation in agile software methodology using human opinion dynamics

Abstract

Agile methodologies provide a structure for highly collaborative software development. Rather than adhering to traditionally long periods of upfront requirements gathering and design before software production, agile teams elicit feedback early on in the process, and deal with the complexities of software development by practicing rapid iterative development from project inception. A major cause of failure of many software projects is the lack of accurate and early cost estimation. Barry Boehm proposed Constructive Cost Model also known as, COCOMO Model which used basic regression formula with parameters derived from historical project data and characteristics of the current project for estimating the cost of software.  This model is a high risk due to low accuracy and lack of reliability. This is where the need of optimization comes in. Various approaches like Genetic Algorithm have already been applied for tuning of the parameters of COCOMO in order to increase it’s accuracy and reliability. Regardless, that humans are the most intelligent social animals, an approach based on crowd dynamics, opinion dynamics, language dynamics is seldom used for optimization. Interaction between humans gives rise to different kind of opinions in a society. The process of opinion formation evolves from collective intelligence emerging from integrative forces of social influence with disintegrative effects of individualization. Opinion dynamics leads to efficient decision making and so, we propose an approach based on human opinion dynamics for effective and accurate software cost estimation.