Java Development Kit
This is the software class dependency network of the JDK 1.6.0.7 framework. The
network is directed. Nodes represent classes. An edge between them indicates
that there exists a dependency between two classes. As there may be multiple
references between classes the network has multiple edges.
Metadata
Statistics
| Size | n = | 6,434
|
| Volume | m = | 150,985
|
| Unique edge count | m̿ = | 53,892
|
| Loop count | l = | 0
|
| Wedge count | s = | 52,676,393
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| Claw count | z = | 92,489,410,361
|
| Cross count | x = | 131,184,856,673,035
|
| Triangle count | t = | 194,842
|
| Square count | q = | 82,893,262
|
| 4-Tour count | T4 = | 873,958,984
|
| Maximum degree | dmax = | 32,530
|
| Maximum outdegree | d+max = | 375
|
| Maximum indegree | d−max = | 32,507
|
| Average degree | d = | 46.933 5
|
| Fill | p = | 0.001 302 06
|
| Average edge multiplicity | m̃ = | 2.801 62
|
| Size of LCC | N = | 6,434
|
| Size of LSCC | Ns = | 77
|
| Relative size of LSCC | Nrs = | 0.011 967 7
|
| Diameter | δ = | 7
|
| 50-Percentile effective diameter | δ0.5 = | 1.611 33
|
| 90-Percentile effective diameter | δ0.9 = | 2.473 00
|
| Median distance | δM = | 2
|
| Mean distance | δm = | 2.188 07
|
| Gini coefficient | G = | 0.750 504
|
| Balanced inequality ratio | P = | 0.201 772
|
| Outdegree balanced inequality ratio | P+ = | 0.266 801
|
| Indegree balanced inequality ratio | P− = | 0.097 029 5
|
| Relative edge distribution entropy | Her = | 0.829 550
|
| Power law exponent | γ = | 1.481 00
|
| Tail power law exponent | γt = | 2.361 00
|
| Tail power law exponent with p | γ3 = | 2.361 00
|
| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 2.821 00
|
| Outdegree p-value | po = | 0.000 00
|
| Indegree tail power law exponent with p | γ3,i = | 1.751 00
|
| Indegree p-value | pi = | 0.012 000 0
|
| Degree assortativity | ρ = | −0.223 025
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| In/outdegree correlation | ρ± = | −0.031 772 5
|
| Clustering coefficient | c = | 0.011 096 5
|
| Directed clustering coefficient | c± = | 0.454 164
|
| Spectral norm | α = | 1,062.14
|
| Operator 2-norm | ν = | 1,045.24
|
| Cyclic eigenvalue | π = | 16.877 2
|
| Algebraic connectivity | a = | 0.401 218
|
| Spectral separation | |λ1[A] / λ2[A]| = | 1.032 18
|
| Reciprocity | y = | 0.008 684 03
|
| Non-bipartivity | bA = | 0.031 173 4
|
| Normalized non-bipartivity | bN = | 0.160 371
|
| Algebraic non-bipartivity | χ = | 0.319 511
|
| Spectral bipartite frustration | bK = | 0.004 788 98
|
| Controllability | C = | 4,232
|
| Relative controllability | Cr = | 0.657 756
|
Plots
Matrix decompositions plots
Downloads
References
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[1]
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Jérôme Kunegis.
KONECT – The Koblenz Network Collection.
In Proc. Int. Conf. on World Wide Web Companion, pages
1343–1350, 2013.
[ http ]
|
KONECT ‣ Networks ‣
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