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The long‐term growth rate of evolving software: Empirical results and implications
Author(s) -
Hatton Les,
Spinellis Diomidis,
van Genuchten Michiel
Publication year - 2017
Publication title -
journal of software: evolution and process
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 29
eISSN - 2047-7481
pISSN - 2047-7473
DOI - 10.1002/smr.1847
Subject(s) - computer science , software development , software , source lines of code , software system , code (set theory) , source code , open source software , software sizing , term (time) , software engineering , software construction , operating system , programming language , physics , set (abstract data type) , quantum mechanics
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.