The Impact of the Object-Oriented Software Evolution on Software Metrics: The Iris Approach

TL;DR

This paper introduces Iris, an automatic approach that analyzes software evolution by examining software variants, demonstrating that software complexity tends to increase over successive releases across multiple projects.

Contribution

The Iris approach uniquely exploits software variants to study the impact of evolution on software metrics, supporting the hypothesis that software grows more complex over time.

Findings

Software complexity increases with evolution.

Iris effectively supports the hypothesis across diverse projects.

Software metrics reflect ongoing complexity growth.

Abstract

The Object-Oriented (OO) software system evolves over the time to meet the new requirements. Based on the initial release of software, the continuous modification of software code leads to software evolution. Software needs to evolve over the time to meet the new user's requirements. Software companies often develop variant software of the original one depends on customers' needs. The main hypothesis of this paper states that the software when it evolves over the time, its code continues to grow, change and become more complex. This paper proposes an automatic approach (Iris) to examine the proposed hypothesis. Originality of this approach is the exploiting of the software variants to study the impact of software evolution on the software metrics. This paper presents the results of experiments conducted on three releases of drawing shapes software, sixteen releases of rhino software, eight releases of mobile media software and ten releases of ArgoUML software. Based on the extracted software metrics, It has been found that Iris hypothesis is supported by the computed metrics.