An Exploration of Power-Law in Use-Relation of Java Software Systems

Ichii, Makoto; Matsushita, Masayuki; Inoue, Katsuro

doi:10.1109/aswec.2008.4483231

Cited by 19 publications

(11 citation statements)

References 23 publications

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“…Concas et al [9] examined 10 properties of 3 software systems and found those properties to have both Pareto and log-normal distributions. Ichii et al [16] examined 4 measures (including two variants of WMC) on 6 systems, finding that in-degree follows a power law while out-degree follows some other heavy-tailed distribution. Louridas et al [23] found power-laws present in the dependencies of software libraries, applications, and system calls in the Linux and FreeBSD operating systems and concluded that power-laws are ubiquitous in software systems.…”

Section: Empirical Findingsmentioning

confidence: 99%

“…Roughly speaking, an approximately scale-free distribution would manifest itself as a straight line on a log-log plot of the connection degree histogram (i.e., number of connections vs. frequency of nodes). Evidence suggests that other distributions produce similar network characteristics [19,8] and that these distributions exist for various relations in procedural and objectoriented software systems [37,26,24,30,35,4,18,15,17,9,23,6,16,14,36,12]. This set of distributions are known as heavy-tailed to differentiate the decay characteristic of their probability mass function from that of typical exponential decay; a significant probability of occurrence exists even at several standard deviations above the mean [8].…”

Section: Introductionmentioning

confidence: 99%

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Can We Avoid High Coupling?

Taube-Schock

Walker

Witten

2011

Lecture Notes in Computer Science

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Abstract. It is considered good software design practice to organize source code into modules and to favour within-module connections (cohesion) over between-module connections (coupling), leading to the oftrepeated maxim "low coupling/high cohesion". Prior research into network theory and its application to software systems has found evidence that many important properties in real software systems exhibit approximately scale-free structure, including coupling; researchers have claimed that such scale-free structures are ubiquitous. This implies that high coupling must be unavoidable, statistically speaking, apparently contradicting standard ideas about software structure. We present a model that leads to the simple predictions that approximately scale-free structures ought to arise both for between-module connectivity and overall connectivity, and not as the result of poor design or optimization shortcuts. These predictions are borne out by our large-scale empirical study. Hence we conclude that high coupling is not avoidable-and that this is in fact quite reasonable.

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Section: Empirical Findingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Can We Avoid High Coupling?

Taube-Schock

Walker

Witten

2011

Lecture Notes in Computer Science

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“…Previous work found that the increase of WMC may lead to a larger LCOM [36,43] , because without specific optimization newly-created methods often have few interactions with all the existing methods. Hence, based on our observation on WMC we guess that there is a positive correlation between k out and LCOM.…”

Section: Correlations Between Cross-level Metricsmentioning

confidence: 99%

“…A comprehensive analysis on structural features of these networks showed that most of them exhibit approximate power-law degree distribution and high clustering across different levels of granularity (viz., package, class and method) [23][24][25][37][38][39][40][41][42][43][44] , which proved that the topological structure of OO software based on the Internet possesses distinct characteristics of complex networks. Based on the ample empirical evidence, software as a complex network (SaaCN) has gradually been recognized within the software engineering community [24][25][45][46] …”

Section: Software Systems As Complex Networkmentioning

confidence: 99%

A Hybrid Set of Complexity Metrics for Large-Scale Object-Oriented Software Systems

et al. 2010

J. Comput. Sci. Technol.

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Ma YT, He KQ, Li B et al. A hybrid set of complexity metrics for large-scale object-oriented software systems. AbstractLarge-scale object-oriented (OO) software systems have recently been found to share global network characteristics such as small world and scale free, which go beyond the scope of traditional software measurement and assessment methodologies. To measure the complexity at various levels of granularity, namely graph, class (and object) and source code, we propose a hierarchical set of metrics in terms of coupling and cohesion -the most important characteristics of software, and analyze a sample of 12 open-source OO software systems to empirically validate the set. Experimental results of the correlations between cross-level metrics indicate that the graph measures of our set complement traditional software metrics well from the viewpoint of network thinking, and provide more effective information about fault-prone classes in practice.

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“…Ichii investigated a distribution of a number of incoming edges and outgoing edges of component graph for a variety of software systems [12]. He reported the distribution of a number of outgoing edges is bounded by a size of class description, however, that of incoming edges is open-ended.…”

Section: Significance Of Use Relation Analysismentioning

confidence: 99%