Building it together: synchronous development in OSS

Xuan, Qi; Filkov, Vladimir

doi:10.1145/2568225.2568238

Cited by 37 publications

(27 citation statements)

References 55 publications

(54 reference statements)

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“…To this end, a first line of works has used data that directly capture communication [13], e.g. via IRC channels [14], E-Mail exchanges [15,16,17,18,19], mailing lists [20], or communication via issue trackers [21,22,23,24,25].…”

Section: Related Workmentioning

confidence: 99%

git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

Gote

Scholtes

Schweitzer

2019

2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)

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Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Most of the studied networks are based on the co-authorship of software artefacts defined at the level of files, modules, or packages. While this approach has led to insights into the social aspects of software development, it neglects detailed information on code changes and code ownership, e.g. which exact lines of code have been authored by which developers, that is contained in the commit log of software projects.Addressing this issue, we introduce git2net, a scalable python software that facilitates the extraction of fine-grained co-editing networks in large git repositories. It uses text mining techniques to analyse the detailed history of textual modifications within files. This information allows us to construct directed, weighted, and time-stamped networks, where a link signifies that one developer has edited a block of source code originally written by another developer. Our tool is applied in case studies of an Open Source and a commercial software project. We argue that it opens up a massive new source of high-resolution data on human collaboration patterns. 1 https://github.com/gotec/git2net © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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Section: Related Workmentioning

confidence: 99%

git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

Gote

Scholtes

Schweitzer

2019

2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)

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“…Finally, performance properties, such as productivity, in terms of number of lines of code written, can also be measured using the state of the produced software. Communication is vital in making collaboration effective [57]. Lack of communication between software developers may introduce more coordination problems [28], and thus the distributed developers do need to maintain awareness of one another to make the OSS projects successful [27].…”

Section: Introductionmentioning

confidence: 99%

Converging Work-Talk Patterns in Online Task-Oriented Communities

2016

Self Cite

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Much of what we do is accomplished by working collaboratively with others, and a large portion of our lives are spent working and talking; the patterns embodied in the alternation of working and talking can provide much useful insight into task-oriented social behaviors. The available electronic traces of the different kinds of human activities in online communities are an empirical goldmine that can enable the holistic study and understanding of these social systems. Open Source Software (OSS) projects are prototypical examples of collaborative, task-oriented communities, depending on volunteers for high-quality work. Here, we use sequence analysis methods to identify the work-talk patterns of software developers in online communities of Open Source Software projects. We find that software developers prefer to persist in same kinds of activities, i.e., a string of work activities followed by a string of talk activities and so forth, rather than switch them frequently; this tendency strengthens with time, suggesting that developers become more efficient, and can work longer with fewer interruptions. This process is accompanied by the formation of community culture: developers’ patterns in the same communities get closer with time while different communities get relatively more different. The emergence of community culture is apparently driven by both “talk” and “work”. Finally, we also find that workers with good balance between “work” and “talk” tend to produce just as much work as those that focus strongly on “work”; however, the former appear to be more likely to continue to be active contributors in the communities.

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“…protein-protein networks 1,2 and brain networks, 3,4 to sociological systems, e.g. collaboration networks 5,6 and communication networks. 7,8 It is being proved that networks as discrete spaces are useful to study various dynamics, such as material and information°ows, 9,10 reaction-di®usion dynamics, example, the network distance between two nodes is always de¯ned as the smallest number of connections included in any path between them 19 while the Euclidean distance between two points is de¯ned as the length of the line segment connecting them.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous multidimensional scaling for complex networks

Xuan

et al. 2015

Int. J. Mod. Phys. C

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Many real-world networks are essentially heterogeneous, where the nodes have di®erent abilities to gain connections. Such networks are di±cult to be embedded into low-dimensional Euclidean space if we ignore the heterogeneity and treat all the nodes equally. In this paper, based on a newly de¯ned heterogeneous distance and a generalized network distance under the constraints of network and triangle inequalities, respectively, we propose a new heterogeneous multidimensional scaling method (HMDS) to embed di®erent networks into proper Euclidean spaces. We¯nd that HMDS behaves much better than the traditional multidimensional scaling method (MDS) in embedding di®erent arti¯cial and real-world networks into Euclidean spaces. Besides, we also propose a method to estimate the appropriate dimensions of Euclidean spaces for di®erent networks, and¯nd that the estimated dimensions are quite close to the real dimensions for those geometrical networks under study. These methods thus can help to better understand the evolution of real-world networks, and have practical importance in network visualization, community detection, link prediction and localization of wireless sensors.

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Building it together: synchronous development in OSS

Cited by 37 publications

References 55 publications

git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

Converging Work-Talk Patterns in Online Task-Oriented Communities

Heterogeneous multidimensional scaling for complex networks

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