This repository contains the reproducibility package (software and data) for the following paper. Les Hatton, Diomidis Spinellis, and Michiel van Genuchten. The long-term growth rate of evolving software: Empirical results and implications. Journal of Software: Evolution and Process, 29(5), May 2017. doi:10.1002/smr.1847 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 (CAGR) 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.