Are developers fixing their own bugs?: Tracing bug-fixing and bug-seeding committers

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 IGI GlobalThe process of fixing software bugs plays a key role in the maintenance activities of a software project. Ideally, code ownership and responsibility should be enforced among developers working on the same artifacts, so that those introducing buggy code could also contribute to its fix. However, especially in FLOSS projects, this mechanism is not clearly understood: in particular, it is not known whether those contributors fixing a bug are the same introducing and seeding it in the first place. This paper analyzes the comm-central FLOSS project, which hosts part of the Thunderbird, SeaMonkey, Lightning extensions and Sunbird projects from the Mozilla community. The analysis is focused at the level of lines of code and it uses the information stored in the source code management system. The results of this study show that in 80% of the cases, the bug-fixing activity involves source code modified by at most two developers. It also emerges that the developers fixing the bug are only responsible for 3.5% of the previous modifications to the lines affected; this implies that the other developers making changes to those lines could have made that fix. In most of the cases the bug fixing process in comm-central is not carried out by the same developers than those who seeded the buggy code.This work has been partially funded by the European Commission, under the ALERT project (ICT-258098)

Estimating development effort in free/open source software projects by mining software repositories: A case study of OpenStack

Because of the distributed and collaborative nature of free/open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially-but not only-because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.Gregorio Robles, Carlos Cervig on and Jes us M. Gonz alez-Barahona, project SobreSale (TIN2011-28110). and The work of Daniel Izquierdo has been funded in part by the Torres Quevedo program (PTQ-12-05577

Parameterizing the competition between homogeneous and heterogeneous freezing in cirrus cloud formation – monodisperse ice nuclei

We present a parameterization of cirrus cloud formation that computes the ice crystal number and size distribution under the presence of homogeneous and heterogeneous freezing. The parameterization is very simple to apply and is derived from the analytical solution of the cloud parcel equations, assuming that the ice nuclei population is monodisperse and chemically homogeneous. In addition to the ice distribution, an analytical expression is provided for the limiting ice nuclei number concentration that suppresses ice formation from homogeneous freezing. The parameterization is evaluated against a detailed numerical parcel model, and reproduces numerical simulations over a wide range of conditions with an average error of 6±33%. The parameterization also compares favorably against other formulations that require some form of numerical integration

Dynamical States of Low Temperature Cirrus

Low ice crystal concentration and sustained in-cloud supersaturation, commonly found in cloud observations at low temperature, challenge our understanding of cirrus formation. Heterogeneous freezing from effloresced ammonium sulfate, glassy aerosol, dust and black carbon are proposed to cause these phenomena; this requires low updrafts for cirrus characteristics to agree with observations and is at odds with the gravity wave spectrum in the upper troposphere. Background temperature fluctuations however can establish a dynamical equilibrium between ice production and sedimentation loss (as opposed to ice crystal formation during the first stages of cloud evolution and subsequent slow cloud decay) that explains low temperature cirrus properties. This newly-discovered state is favored at low temperatures and does not require heterogeneous nucleation to occur (the presence of ice nuclei can however facilitate its onset). Our understanding of cirrus clouds and their role in anthropogenic climate change is reshaped, as the type of dynamical forcing will set these clouds in one of two preferred microphysical regimes with very different susceptibility to aerosol

A new bound of the ℒ2[0, T]-induced norm and applications to model reduction

We present a simple bound on the finite horizon ℒ2/[0, T]-induced norm of a linear time-invariant (LTI), not necessarily stable system which can be efficiently computed by calculating the ℋ∞ norm of a shifted version of the original operator. As an application, we show how to use this bound to perform model reduction of unstable systems over a finite horizon. The technique is illustrated with a non-trivial physical example relevant to the appearance of time-irreversible phenomena in statistical physics

Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate

With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To communicate effectively through Twitter, policy makers need to understand how influence and interest propagate within its network of users. In this chapter we use graph-theoretic methods to analyse the Twitter debate surrounding NHS Englands controversial care.data scheme. Directionality is a crucial feature of the Twitter social graph - information flows from the followed to the followers - but is often ignored in social network analyses; our methods are based on the behaviour of dynamic processes on the network and can be applied naturally to directed networks. We uncover robust communities of users and show that these communities reflect how information flows through the Twitter network. We are also able to classify users by their differing roles in directing the flow of information through the network. Our methods and results will be useful to policy makers who would like to use Twitter effectively as a communication medium

Parameterizing the competition between homogeneous and heterogeneous freezing in ice cloud formation – polydisperse ice nuclei

This study presents a comprehensive ice cloud formation parameterization that computes the ice crystal number, size distribution, and maximum supersaturation from precursor aerosol and ice nuclei. The parameterization provides an analytical solution of the cloud parcel model equations and accounts for the competition effects between homogeneous and heterogeneous freezing, and, between heterogeneous freezing in different modes. The diversity of heterogeneous nuclei is described through a nucleation spectrum function which is allowed to follow any form (i.e., derived from classical nucleation theory or from observations). The parameterization reproduces the predictions of a detailed numerical parcel model over a wide range of conditions, and several expressions for the nucleation spectrum. The average error in ice crystal number concentration was −2.0±8.5% for conditions of pure heterogeneous freezing, and, 4.7±21% when both homogeneous and heterogeneous freezing were active. The formulation presented is fast and free from requirements of numerical integration

Cellular memory enhances bacterial chemotactic navigation in rugged environments

The response of microbes to external signals is mediated by biochemical networks with intrinsic time scales. These time scales give rise to a memory that impacts cellular behaviour. Here we study theoretically the role of cellular memory in Escherichia coli chemotaxis. Using an agent-based model, we show that cells with memory navigating rugged chemoattractant landscapes can enhance their drift speed by extracting information from environmental correlations. Maximal advantage is achieved when the memory is comparable to the time scale of fluctuations as perceived during swimming. We derive an analytical approximation for the drift velocity in rugged landscapes that explains the enhanced velocity, and recovers standard Keller–Segel gradient-sensing results in the limits when memory and fluctuation time scales are well separated. Our numerics also show that cellular memory can induce bet-hedging at the population level resulting in long-lived, multi-modal distributions in heterogeneous landscapes

Emergence of slow-switching assemblies in structured neuronal networks

Unraveling the interplay between connectivity and spatio-temporal dynamics in neuronal networks is a key step to advance our understanding of neuronal information processing. Here we investigate how particular features of network connectivity underpin the propensity of neural networks to generate slow-switching assembly (SSA) dynamics, i.e., sustained epochs of increased firing within assemblies of neurons which transition slowly between different assemblies throughout the network. We show that the emergence of SSA activity is linked to spectral properties of the asymmetric synaptic weight matrix. In particular, the leading eigenvalues that dictate the slow dynamics exhibit a gap with respect to the bulk of the spectrum, and the associated Schur vectors exhibit a measure of block-localization on groups of neurons, thus resulting in coherent dynamical activity on those groups. Through simple rate models, we gain analytical understanding of the origin and importance of the spectral gap, and use these insights to develop new network topologies with alternative connectivity paradigms which also display SSA activity. Specifically, SSA dynamics involving excitatory and inhibitory neurons can be achieved by modifying the connectivity patterns between both types of neurons. We also show that SSA activity can occur at multiple timescales reflecting a hierarchy in the connectivity, and demonstrate the emergence of SSA in small-world like networks. Our work provides a step towards understanding how network structure (uncovered through advancements in neuroanatomy and connectomics) can impact on spatio-temporal neural activity and constrain the resulting dynamics.Comment: The first two authors contributed equally -- 18 pages, including supplementary material, 10 Figures + 2 SI Figure