logo
Kurashizu Blogwhere ideas flow
  • Home
  • News
  • Blog
  • About
  • Home
  • News
  • Blog
  • About

© 2026 Kurashizu. All rights reserved.

Admin·New Post·Service Status
Powered by Cloudflare·30.10.26
← Back to news

More Than a Gigabuck: Estimating GNU/Linux's Size (2001)

Original article
dwheeler.com|3 points|0 comments|by bilegeek|Sep 19, 2026

Beyond the Billion-Dollar Mark: Analyzing the Scale of GNU/Linux (2001)

Author: David A. Wheeler (dwheeler@dwheeler.com)
Date: June 20, 2001 | Version: 1.0


Executive Summary

This research examines the volume of source code within the GNU/Linux ecosystem, utilizing Red Hat Linux 7.1 as the primary benchmark. The findings suggest a staggering economic reality: if this distribution were developed using traditional, proprietary American corporate methods, the cost would exceed $1 billion (a "Gigabuck").

Comparative Growth: RH 6.2 vs. RH 7.1

The expansion of the OS over a single year is significant. We can see the shift in scale here:

MetricRed Hat Linux 6.2Red Hat Linux 7.1Change
Development Cost\approx \600 \text{ million}$>\1,000 \text{ million}$↑≈66%\uparrow \approx 66\%↑≈66%
Physical SLOC≈17 million\approx 17 \text{ million}≈17 million>30 million> 30 \text{ million}>30 million↑≈76%\uparrow \approx 76\%↑≈76%
Effort (Person-Years)4,5004,5004,5008,0008,0008,000↑≈77%\uparrow \approx 77\%↑≈77%

The overall growth in size, effort, and theoretical cost is calculated as: Growth>60%\text{Growth} > 60\%Growth>60%

This surge is attributed to the increasing availability and maturity of free and open-source software globally.


Technical Breakdown

Primary Components

The distribution is composed of several massive projects. The largest contributors, ranked by size, include:

  1. Linux Kernel (including all device drivers)
  2. Mozilla (The suite containing the browser, email client, and HTML editor)
  3. X-Windows (The GUI infrastructure)
  4. gcc (The compiler)
  5. gdb (The debugger)
  6. Basic binary utilities
  7. Emacs (The extensible editor)
  8. LAPACK (Fortran linear algebra library)
  9. Gimp (Image manipulation)
  10. MySQL (Relational database)

Language Distribution

The linguistic makeup of the code has shifted. While C remains dominant, C++ has seen a notable increase.

Full Language List (Sorted by SLOC):

  • C (81% →\rightarrow→ 71%)
  • C++ (8% →\rightarrow→ 15%)
  • Shell (incl. ksh)
  • Lisp, Assembly, Perl, Fortran, Python, Tcl, Java, yacc/bison, expect, lex/flex, awk, Objective-C, Ada, C shell, Pascal, and sed.

Licensing and Legal Framework

The distribution is heavily rooted in copyleft philosophy.

  • GPL Only: Slightly over 50% of the software.
  • Copyleft (GPL or LGPL): 63% of the total code.

Definition: "Open source" or "free software" refers to programs where the source code is accessible, allowing users to view, modify, and redistribute the work without paying royalties or facing restrictive limitations.


Context and Market Analysis

The Rise of Linux

GNU/Linux has evolved from an obscure project into a dominant market force.

  • Server Dominance: One study [Zoebelein 1999] indicated Linux is the most used OS for Internet servers.
  • Market Share: IDC [Shankland 2000a] reported that in 1999, 25% of server OS purchases were Linux, trailing only Windows NT (38%).

Reliability Benchmarks

The popularity of Linux isn't just about the price tag; it's about stability.

  1. Component Failure: A 1995 study [Miller 1995] showed GNU/Linux components had a failure rate of only 6% to 9%, compared to 23% for proprietary Unix systems.
  2. Uptime: A 1999 ZDnet experiment [Vaughan-Nichols 1999] found that under typical intranet loads, Windows NT crashed every six weeks, while Linux systems never crashed.

Linux Stability Concept


Methodology and Goals

The author's objective for this paper was to provide a quantitative analysis of the OS size, as very little published data exists outside of the "Halloween Documents" produced by Microsoft.

Project Goals:

  • Measure SLOC for Red Hat Linux 7.1.
  • Compare results against Red Hat Linux 6.2.
  • Estimate proprietary development costs using the COCOMO model.
  • Analyze language and license distribution.

To calculate the effort, the COCOMO model was applied:

// Conceptual COCOMO Effort Calculation
double effort = a * pow(kloc, b); 
// where kloc = thousands of lines of code

For further details, visit http://www.dwheeler.com/sloc.