2003/06/24 by Alessandro P. S. de Moura, Ying‐Cheng Lai, Ying-Cheng Lai +1
Computer Science · Decision Sciences · Engineering · Physics and Astronomy · #Complex Network Analysis Techniques #Complex network #Computer program #Computer science #Distributed computing #Domain (mathematical analysis) #Engineering #Game Theory and Applications #Node (physics) #Programming language #Quantum Computing Algorithms and Architecture #Scale (ratio) #Scale-free network #Software #Theoretical computer science #World Wide Web #cond-mat.dis-nn #cs.GL
paper · pdf · doi:10.1103/physreve.68.017102
published as Phys. Rev. E 68, 017102 (2003) · 4 pages, 1 figure, to appear in Phys. Rev. E
arxiv created 2003/06/24 · openalex publication_date 2003/07/15 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.