Cristina Monni

A study of the community structure of a complex software network

This paper presents a case study of a large software system, Netbeans 6.0, made of independent subsystems, which are analyzed as complex software networks. Starting from the source code we built the associated software graphs, where classes represent graph nodes and inter-class relationships represent graph edges. We computed various metrics for the software systems and found interdependences with various quantities computed by mean of the complex network analysis. In particular we found that the number of communities in which the software networks can be partitioned and their modularity, average path length and mean degree can be related to the amount of bugs detected in the system. This result can be useful to provide indications about the fault proneness of software clusters in terms of quantities related to the associated graph structure.

High energy string–brane scattering for massive states

Abstract String–brane interactions provide an ideal framework to study the dynamics of the massive states of the string spectrum in a non-trivial background. We present here an analysis of tree-level amplitudes for processes in which an NS–NS string state from the leading Regge trajectory scatters from a D-brane into another state from the leading Regge trajectory, in general of a different mass, at high energies and small scattering angles. This is done by using world-sheet OPE methods and effective vertex operators. We find that this class of processes has a universal dependence on the energy of the projectile. We then compare the result for these inelastic processes with that which one would obtain from the eikonal operator in a non-trivial test of its ability to describe transitions between different string mass levels. The two are found to be in agreement.

BPS-like bound and thermodynamics of the charged BTZ black hole

The charged Banados-Teitelboim-Zanelli (BTZ) black hole is plagued by several pathologies: (a) Divergent boundary terms are present in the action; hence, we have a divergent black-hole mass. (b) Once a finite, renormalized, mass M is defined, black-hole states exist for arbitrarily negative values of M. (c) There is no upper bound on the charge Q. We show that these pathological features are an artifact of the renormalization procedure. They can be completely removed by using an alternative renormalization scheme leading to a different definition M{sub 0} of the black-hole mass, which is the total energy inside the horizon. The new mass satisfies a BPS-like bound M{sub 0}{>=}({pi}/2)Q{sup 2}, and the heat capacity of the hole is positive. We also discuss the black-hole thermodynamics that arises when M{sub 0} is interpreted as the internal energy of the system. We show, using three independent approaches (black-hole thermodynamics, Einstein equations, and Euclidean action formulation), that M{sub 0} satisfies the first law if a term describing the mechanical work done by the electrostatic pressure is introduced.

Are refactoring practices related to clusters in java software

Refactoring is widely used among the practices of Agile software development. In this preliminary work we present an empirical study carried out on several releases of 5 software systems written in Java. We focus our attention on the effect of refactoring activities on the topology of the software network. We find that refactoring activities involve classes linked together into clusters inside the software network and the clusters may be modified in different ways by the refactoring activity. This could lead to significative changes in source code, whose knowledge could be valuable for people involved in software development.

Software quality and community structure in Java software networks

We present a study of 600 Java software networks with the aim of characterizing the relationship among their defectiveness and community metrics. We analyze the community structure of such networks, defined as their topological division into subnetworks of densely connected nodes. A high density of connections represents a higher level of cooperation between classes, so a well-defined division in communities could indicate that the software system has been designed in a modular fashion and all its functionalities are well separated. We show how the community structure can be an indicator of well-written, high quality code by retrieving the communities of the analyzed systems and by ranking their division in communities through the built-in metric called modularity. We found that the software systems with highest modularity possess the majority of bugs, and tested whether this result is related to some confounding effect. We found two power laws relating the maximum defect density with two different metric...

Clustering of defects in Java software systems

In this paper we present a case study about the clustering of maintenance activities applied on large software systems, from the complex networks perspective. We analyze several releases of two large Open Source Java software systems, using data extracted from Software Configuration Management systems and from Issue Tracking systems (ITS). We find that Java files affected by maintenance activity are likely to be connected with each other, forming interconnected clusters inside the software network associated to the software system. This means that Java files interested by the maintenance activities requested on ITS are likely to be connected each other through dependencies at the source code level. The information carried by the clusters of Java files may be used to improve strategies for large maintenance operations. Since the tendency to form clusters can vary across different systems, such analysis can also be a useful indicator of the impact of defects on source code files in different software systems.

Mass bound and thermodynamical behaviour of the charged BTZ Black Hole

The charged Banados-Teitelboim-Zanelli (BTZ) black hole displays divergent boundary terms in the action, which lead to a divergent black hole mass. Once a finite, regularized, mass M is defined black hole states exist for arbitrarily negative values of M, moreover there is no upper bound on the U(1) charge Q. We show that these pathologies can be completely removed by using an alternative renormalization procedure for the black hole mass and defining a new mass Mo, which is the total energy inside the horizon. The new mass satisfies a BPS-like bound Mo ≥ Q2 and the heat capacity of the hole is positive. We also discuss the black hole thermodynamics that arises when Mo is interpreted as the internal energy of the system. We show, using three independent approaches (black hole thermodynamics, Einstein equations, Euclidean action formulation) that Mo satisfies the first law if a term describing the mechanical work done by the electrostatic pressure is introduced.

Fitting long-tailed distribution to empirical data

Power laws can fit a variety of distributions coming from real data, so a systematic approach to the measurement of the accuracy of fitting algorithms is essential. We discuss the limits of the analysis of empirical fat‐tailed distributions, which can describe a variety of evolving systems, both natural and man‐made. An algorithm to fit fat‐tailed distributions is presented and tested against samplings of the power law, the Yule, the log‐normal, and Weibull distributions. We compute the parameters defining the shape of each distribution and test the results against simulations. We compare our method with another state‐of‐the‐art technique to estimate the parameters of empirical distributions. The accuracy of the estimations is discussed, and we conclude that our method based on a weighted iterated χ2 test performs better than the other. Our algorithm is general and can be applied to any numerical dataset.

Refactoring Clustering in Java Software Networks

We present a study on the refactoring activities performed during the evolution of 7 popular Java open source software systems, using a complex network approach. We find that classes affected by refactorings are more likely to be interlinked than others, forming connected subgraphs. Our results show that in a software network, classes linked to refactored classes are likely to be refactored themselves. This result is meaningful because knowing how refactored classes are arranged inside a network could be useful to support developers in maintenance and refactoring activities.