New Failure Rate Model for Iterative Software Development Life Cycle Process

TL;DR

This paper introduces a new failure rate model tailored for iterative software development, incorporating varying needs and imperfect debugging, validated on Eclipse and JDT datasets, outperforming existing models in most cases.

Contribution

A novel failure rate model specifically designed for iterative development processes, integrating a modulation factor and validated with advanced optimization techniques.

Findings

Outperforms existing models in 83.33% of Eclipse dataset iterations.

Achieves better fit in 77.77% of JDT dataset iterations.

Effectively models fault introduction and removal during iterative development.

Abstract

Software reliability models are one of the most generally used mathematical tool for estimation of reliability, failure rate and number of remaining faults in the software. Existing software reliability models are designed to follow waterfall software development life cycle process. These existing models do not take advantage of iterative software development process. In this paper, a new failure rate model centered on iterative software development life cycle process has been developed. It aims to integrate a new modulation factor for incorporating varying needs in each phase of iterative software development process. It comprises imperfect debugging with the possibility of fault introduction and removal of multiple faults in an interval as iterative development of the software proceeds. The proposed model has been validated on twelve iterations of Eclipse software failure dataset and nine iterations of Java Development toolkit (JDT) software failure dataset. Parameter estimation for the proposed model has been done by hybrid Particle Swarm Optimization and Gravitational Search Algorithm. Experimental results in-terms of goodness-of-fit shows that proposed model has outperformed Jelinski Moranda, Shick Wolverton, Goel Okummotto Imperfect debugging, GS Mahapatra, Modified Shick Wolverton in 83.33 % of iterations for eclipse dataset and 77.77% of iterations for JDT dataset.