The long-term growth rate of evolving software: Empirical results and implications

Les Hatton, Diomidis Spinellis*, Michiel van Genuchten

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

19 Citations (Scopus)

Abstract

The amount of code in evolving software-intensive systems appears to be growing relentlessly, affecting products and entire businesses. Objective figures quantifying the software code growth rate bounds in systems over a large time scale can be used as a reliable predictive basis for the size of software assets. We analyze a reference base of over 404 million lines of open source and closed software systems to provide accurate bounds on source code growth rates. We find that software source code in systems doubles about every 42 months on average, corresponding to a median compound annual growth rate of 1.21 ± 0.01. Software product and development managers can use our findings to bound estimates, to assess the trustworthiness of road maps, to recognise unsustainable growth, to judge the health of a software development project, and to predict a system's hardware footprint.

Original languageEnglish
Article numbere1847
JournalJournal of Software: Evolution and Process
Volume29
Issue number5
DOIs
Publication statusPublished - May 2017
Externally publishedYes

Keywords

  • CAGR
  • code growth rate
  • compound annual growth rate
  • empirical study
  • software evolution

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