On evidence supporting the FEAST hypothesis and the laws of software evolution

Abstract

Abstract| As part of its study of the impact of feedback in the global software process on software product evolution, the FEAST 1 project has examined metric data relating to various systems in di erent application areas. High level similarities in the growth trends of the systems studied support the FEAST hypothesis. Inter alia, the results provide evidence compatible with the laws of software evolution, subject only to minor adjustments of the latter.

Exploring the Prevalence and Evolution of Android Concerns: A Community Viewpoint

“…Lehman et al 's work has been at the forefront of these efforts, and culminated in the laws of software evolution [24], [25], various metrics for studying software evolution [33] and a theory of software evolution [34]. In general, Lehman and his colleagues noted that software systems growth followed a smooth long range trend, with superimposed ripple and a region of instability or chaotic behavior [34] -this pattern has been replicated in the study of many systems of varying application areas, sizes and organizational domains over the last four decades [35].…”

Software architecture evolution through evolvability analysis

“…There have been a large number of studies published on OSS characteristics and evolution patterns by examining sequences of code versions or releases using statistical analysis. Meanwhile, the easily accessible data about different aspects of OSS projects also provides researchers with immense number of opportunities to validate the prior studies of proprietary software evolution [112] and to study how evolvability has been addressed in OSS evolution.…”

“…There exist diverse interpretations of rate of growth. For instance, one assumption in some empirical studies [159,162] on software evolution, as also suggested by Lehman [112], is to analyze and plot growth data with respect to the release sequence number (RSN).…”

“…-System change Separating the characterizations of system growth and system change is a challenge [112]. A variety of change metrics can be used.…”

“…-Size Lehman suggests using the number of modules to quantify program size, as he argues that this metric is more consistent than considering source lines of code [112]. However, there are different interpretations of a module.…”