Our modern infrastructure relies increasingly on computation and computers. Accompanying this is a rise in the prevalence and complexity of computer programs. Current software systems (composed of an interacting collection of programs, functions, classes, etc.) implement a tremendous range of functionality, from simple mathematical operations to intricate control systems. Software systems are inherently extendable and tend to gain new functionality over time. Modern computers and programming languages are Turing complete and, thus, capable of implementing any computable function no matter how complex. The interdependencies between the elements of a software system form a network, and, therefore, we believe software systems can provide useful prototypic examples of how to build complex networked systems which require minimal maintenance, are robust bugs to and yet are readily extendable. Thus we ask: What makes for good design in software systems?
We are particularly interested in open source software (OSS)—software with source code that is freely available for download and modification. A typical OSS project is a collaborative effort by volunteers, with no central authority assigning development tasks. Instead individuals, or self-organized teams of developers, fix bugs and maintain and extend the code. In OSS, modularity is essential (1; 2), and remarkably, the software resulting from an OSS process can rival or even surpass the quality of commercial software [3; 4].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
E. S. Raymond. The Cathedral & the Bazaar. O'Reilly and Associates, Sebastopol, CA, 1999.
T. O'Reilly. Lessons from open source software development. Communications of the ACM, 42(4), 1999.
P. Ball. Openness makes software better sooner. Nature, June 25, 2003.
D. Challet and Y. Le Du. Microscopic model of software bug dynamics: Closed source versus open source. International Journal of Reliability, Quality and Safety Engineering, 12(6), 2005.
M. Fowler. Refactoring: Improving the Design of Existing Programs. Addison-Wesley, Reading, MA, 1999.
A. A. Gorshenev and Yu. M. Pis'mak. Punctuated equilibrium in software evolution. Phys. Rev. E, 70(6):067103, 2004.
Software Maintenance Costs and references therein, http://www.cs.jyu.fi/∼koskinen/smcosts.htm.
S. Valverde, R. Ferrer Cancho, and R. V. Solé. Scale-free networks from optimal design. Europhys. Lett., 60(4):512–517, 2002.
C. R. Myers. Software systems as complex networks: Structure, function, and evolvability of software collaboration graphs. Phys. Rev. E, 68:046116, 2003.
A. MacCormack, J. Rusnak, and C. Y. Baldwin. Exploring the structure of complex software designs: An empirical study of open source and proprietary code. Management Science, 52(7), 2006.
Z. M. Saul, V. Filkov, P. T. Devanbu, and C. Bird. Recommending random walks. In Proceedings ESEC/SIGSOFT FSE, pages 15–24, 2007.
http://www.grammatech.com/products/codesurfer/overview.html.
S. B. Seidman. Network structure and minimum degree. Social Networks, 5:269–287, 1983.
B. Bollobas. The evolution of sparse graphs. In Graph Theory and Combinatorics, pages 35–57. Academic Press, New York, 1984.
S. Valverde and R. V. Solé. Hierarchical small worlds in software architecture. In Dynamics of Continuous Discrete and Impulsive Systems: Series B; Applications and Algorithms, volume 14, pages 1–11, 2007.
G. Baxter, M. Frean, J. Noble, M. Rickerby, H. Smith, M. Visser, H. Melton, and E. Tempero. Understanding the shape of Java software. In OOPSLA '06: Proceedings of the 21st Annual ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications, pages 397–412, New York, NY, USA, 2006. ACM.
J. N. Warfield. Binary matrices in system modeling. IEEE Transactions on Systems, Man, and Cybernetics, 3:441–449, 1973.
D. Sharman and A. Yassine. Characterizing complex product architectures. Systems Engineering Journal, 7(1), 2004.
P. Erdós and A. Rényi. On random graphs. Publicationes Mathematicae, 6:290–297, 1959.
P. Erdós and A. Rényi. On the evolution of random graphs. Publ. Math. Inst. Hungar. Acad. Sci., 5(17), 1960.
M. Molloy and B. Reed. A critical point for random graphs with a given degree sequence. Random Struct. Alg., 6:161–179, 1995.
M. E. J. Newman, S. H. Strogatz, and D. J. Watts. Random graphs with arbitrary degree distributions and their applications. Phys. Rev. E, 64:026118, 2001.
T. A. B. Snijders. Markov chain Monte Carlo estimation of exponential random graph models. Journal of Social Structure, 3(2), 2002.
C. J. Anderson, S. Wasserman, and B. Crouch. A p* primer: Logit models for social networks. Social Networks, 21:37–66, 1999.
D. Kaplan. The Sage Handbook of Quantitative Methodology for the Social Sciences. Sage Publications Inc., London, 2004.
C. Infante-Rivard, C. R. Weinberg, and M. Guiguet. Xenobiotic-metabolizing genes and small-for-gestational-age births: Interaction with maternal smoking. Epidemiology, 17(1):38–46, 2006.
The R Project for Statistical Computing, http://www.r-project.org.
M. S. Handcock, D. R. Hunter, C. T. Butts, S. M. Goodreau, and M. Morris. statnet: An r package for the statistical modeling of social networks, 2003. http://www.csde.washington.edu/statnet.
T. A. B. Snijders, P. E. Pattison, G. L. Robins, and M. S. Handcock. New specifications for exponential random graph models. Sociological Methodology, 99–153 2006.
S. Konishi and G. Kitagawa. Information Criteria and Statistical Modeling. Springer, New York, 2008.
R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon. Network motifs: Simple building blocks of complex networks. Science, 298:824–827, 2002.
S. Valverde and R. V. Solé. Network motifs in computational graphs: A case study in software architecture. Phys. Rev. E, 72:026107, 2005.
D. R. Hunter and M. S. Handcock. Inference in curved exponential family models for networks. Technical report, Penn State Department of Statistics, 2004. Available from http://www.stat.psu.edu/reports/2004/.
Acknowledgements
We are indebted to Christian Bird for supplying the call graph data which is central to our analysis and to Premkumar Devanbu for many useful discussions. This work was funded in part by the National Science Foundation under Grant No. IIS-0613949.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Birkhäuser Boston, a part of Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Wen, H., D’Souza, R., Saul, Z., Filkov, V. (2009). Evolution of Apache Open Source Software. In: Ganguly, N., Deutsch, A., Mukherjee, A. (eds) Dynamics On and Of Complex Networks. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4751-3_12
Download citation
DOI: https://doi.org/10.1007/978-0-8176-4751-3_12
Published:
Publisher Name: Birkhäuser Boston
Print ISBN: 978-0-8176-4750-6
Online ISBN: 978-0-8176-4751-3
eBook Packages: Computer ScienceComputer Science (R0)