### Abstract

A large computer program is typically divided into many hundreds or even thousands of smaller units, whose logical connections define a network in a natural way. This network reflects the internal structure of the program, and defines the "information flow" within the program. We show that (1) due to its growth in time this network displays a scale-free feature in that the probability of the number of links at a node obeys a power-law distribution, and (2) as a result of performance optimization of the program the network has a small-world structure. We believe that these features are generic for large computer programs. Our work extends the previous studies on growing networks, which have mostly been for physical networks, to the domain of computer software.

Original language | English |
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Article number | 017102 |

Number of pages | 4 |

Journal | Physical Review. E, Statistical, Nonlinear and Soft Matter Physics |

Volume | 68 |

Issue number | 1 |

DOIs | |

Publication status | Published - Jul 2003 |

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### Keywords

- complex networks
- wide-web
- evolving networks
- growing networks
- connectivity
- emergence
- dynamics
- topology
- physics
- model

### Cite this

*Physical Review. E, Statistical, Nonlinear and Soft Matter Physics*,

*68*(1), [017102]. https://doi.org/10.1103/PhysRevE.68.017102

**Signatures of small-world and scale-free properties in large computer programs.** / de Moura, A P S ; Lai, Y C ; Motter, A E ; Lai, Ying-Cheng.

Research output: Contribution to journal › Article

*Physical Review. E, Statistical, Nonlinear and Soft Matter Physics*, vol. 68, no. 1, 017102. https://doi.org/10.1103/PhysRevE.68.017102

}

TY - JOUR

T1 - Signatures of small-world and scale-free properties in large computer programs

AU - de Moura, A P S

AU - Lai, Y C

AU - Motter, A E

AU - Lai, Ying-Cheng

PY - 2003/7

Y1 - 2003/7

N2 - A large computer program is typically divided into many hundreds or even thousands of smaller units, whose logical connections define a network in a natural way. This network reflects the internal structure of the program, and defines the "information flow" within the program. We show that (1) due to its growth in time this network displays a scale-free feature in that the probability of the number of links at a node obeys a power-law distribution, and (2) as a result of performance optimization of the program the network has a small-world structure. We believe that these features are generic for large computer programs. Our work extends the previous studies on growing networks, which have mostly been for physical networks, to the domain of computer software.

AB - A large computer program is typically divided into many hundreds or even thousands of smaller units, whose logical connections define a network in a natural way. This network reflects the internal structure of the program, and defines the "information flow" within the program. We show that (1) due to its growth in time this network displays a scale-free feature in that the probability of the number of links at a node obeys a power-law distribution, and (2) as a result of performance optimization of the program the network has a small-world structure. We believe that these features are generic for large computer programs. Our work extends the previous studies on growing networks, which have mostly been for physical networks, to the domain of computer software.

KW - complex networks

KW - wide-web

KW - evolving networks

KW - growing networks

KW - connectivity

KW - emergence

KW - dynamics

KW - topology

KW - physics

KW - model

U2 - 10.1103/PhysRevE.68.017102

DO - 10.1103/PhysRevE.68.017102

M3 - Article

VL - 68

JO - Physical Review. E, Statistical, Nonlinear and Soft Matter Physics

JF - Physical Review. E, Statistical, Nonlinear and Soft Matter Physics

SN - 1539-3755

IS - 1

M1 - 017102

ER -