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

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. KEYWORDS CAGR, code growth rate, compound annual growth rate, empirical study, software evolution 1 merely noise when we are trying to estimate the actual growth of a source code asset. When applied to the avionic systems above, flight software had a CAGR of 1.18 over a period of 53 years. Robotic space flights had a CAGR of 1.17 between 1975 (Viking, 5000 lines of code) and 2005 J Softw Evol Proc. 2017;29:e1847.wileyonlinelibrary.com/journal/smr

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