Using normalized compression distance to measure the evolutionary stability of software systems

Software evolutionary stability has become an important issue in software maintenance and evolution. It is directly related to software reusability, maintainability and evolvability. In reported prior research, software evolutionary stability has been measured with architecture-level metrics, including reference points and program-level metrics, such as number of modules and number of lines of code. In this paper, information-level metrics based on Kolmogorov complexity are used to measure the differences between versions of software products. Using normalized compression distance, various evolutionary stability metrics of software artifacts are defined: version stability, branch stability, structure stability and aggregate stability. Case studies are performed on two open-source products, Apache HTTP server and Apache Ant build tool. The results from this study show that information-level evolutionary stability metrics can be used together with architecture-level metrics and program-level metrics to assist monitoring the software evolution process, as well as identifying stable or unstable software artifacts.

I. Introduction

Software products must evolve in order to correct existing defects, provide new functionalities, adapt to new environments and increase their nonfunctional qualities, such as security, maintainability, performance, etc. As the size of the software product grows, maintenance becomes the most complicated activity in terms of time, effort and cost. Considerable research has been focused on understanding software evolution in order to reduce evolution complexity and evolution cost [1]–[5].