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26th Annual International Computer Software and Applications Conference
Investigating Large Software System Evolution: The Linux Kernel
Oxford, England
August 26-August 29
ISBN: 0-7695-1727-7
ASCII Text
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E. Merlo, M. Dagenais, P. Bachand, J. S. Sormani, S. Gradara, G. Antoniol, "Investigating Large Software System Evolution: The Linux Kernel," Computer Software and Applications Conference, Annual International, pp. 421, 26th Annual International Computer Software and Applications Conference, 2002.
 
 
BibTex
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@article{ 10.1109/CMPSAC.2002.1045038,
author = {E. Merlo and M. Dagenais and P. Bachand and J. S. Sormani and S. Gradara and G. Antoniol},
title = {Investigating Large Software System Evolution: The Linux Kernel},
journal ={Computer Software and Applications Conference, Annual International},
volume = {0},
year = {2002},
issn = {0730-3157},
pages = {421},
doi = {http://doi.ieeecomputersociety.org/10.1109/CMPSAC.2002.1045038},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer Software and Applications Conference, Annual International
TI - Investigating Large Software System Evolution: The Linux Kernel
SN - 0730-3157
SP
EP
A1 - E. Merlo,
A1 - M. Dagenais,
A1 - P. Bachand,
A1 - J. S. Sormani,
A1 - S. Gradara,
A1 - G. Antoniol,
PY - 2002
KW - software evolution
KW - software metrics
KW - clone analysis
KW - project management
VL - 0
JA - Computer Software and Applications Conference, Annual International
ER -
 
E. Merlo, École Polytechnique de Montréal
M. Dagenais, École Polytechnique de Montréal
P. Bachand, École Polytechnique de Montréal
J. S. Sormani, École Polytechnique de Montréal
S. Gradara, University of Sannio
G. Antoniol, University of Sannio

Large multi-platform, multi-million lines of codes software systems evolve to cope with new platform or to meet user ever changing needs. While there has been several studies focused on the similarity of code fragments or modules, few studies addressed the need to monitor the overall system evolution. Meanwhile, the decision to evolve or to refactor a large software system needs to be supported by high level information, representing the system overall picture, abstracting from unnecessary details.

This paper proposes to extend the concept of similarity of code fragments to quantify similarities at the release/system level. Similarities are captured by four software metrics representative of the commonalities and differences within and among software artifacts.

To show the feasibility of characterizing large software system with the new metrics, 365 releases of the Linux kernel were analyzed. The metrics, the experimental results as well as the lessons learned are presented in the paper.

Index Terms:
software evolution, software metrics, clone analysis, project management
Citation:
E. Merlo, M. Dagenais, P. Bachand, J. S. Sormani, S. Gradara, G. Antoniol, "Investigating Large Software System Evolution: The Linux Kernel," compsac, pp.421, 26th Annual International Computer Software and Applications Conference, 2002
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