Heard it through the Gitvine: an empirical study of tool diffusion across the npm ecosystem

Lamba, Hemank; Trockman, Asher; Armanios, Daniel Erian; Kästner, Christian; Miller, Heather; Vasilescu, Bogdan

doi:10.1145/3368089.3409705

Cited by 11 publications

(6 citation statements)

References 89 publications

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“…Through a large-scale empirical analysis, we found that developers, irrespective of their experience level, use emojis in every step of a conversation. We also found that emoji usage has a statistically significant associ- emojis are more likely to attract users and how that is associated with emoji usage di↵usion [70] in di↵erent levels (threads, projects, etc.). We also provide actionable implications for researchers, tool builders, and practitioners to harness the results of our study.…”

Section: Discussionmentioning

confidence: 66%

An empirical study of emoji use in software development communication

Rong

Wang

Mannan

et al. 2022

Information and Software Technology

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Section: Discussionmentioning

confidence: 66%

An empirical study of emoji use in software development communication

Rong

Wang

Mannan

et al. 2022

Information and Software Technology

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“…Our model provides a solid foundation for future research and can be easily extended, for example with probability 9 . Our model can also be applied in other research beyond software engineering for new research on informationencoding communication networks.…”

Section: Discussionmentioning

confidence: 99%

“…Lamba et al used a multi-layered time-dependent graph for investigating the tool diffusion of 12 quality assurance tools within the npm ecosystem [9]-without explicitly using this terminology. Although there are several similarities to our work on the first sight, the used theory framework on the diffusion of innovations by Rogers does not apply on the general case of communication as Rogers states: Diffusion of innovations is "a special type of communication, in that the messages are concerned with new ideas.…”

Section: Modelling Communication In Software Engineering Researchmentioning

confidence: 99%

Only Time Will Tell: Modelling Information Diffusion in Code Review with Time-Varying Hypergraphs

Dorner,

Šmite,

Mendez

et al. 2021

Preprint

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In this manuscript, we present a novel model based on time-varying hypergraphs for rendering communication networks in software engineering as distributed and self-organizing information repositories, capable of encoding and decoding information over time. Our model overcomes the inherent limitations of traditional, static graph-based models and enables research on the time-dependent spread of information, the so-called information diffusion, within those networks. We perform a discrete-event computer simulation rendering an arbitrary information diffusion in a communication network typical for software engineering, namely code review, in order to (1) present an empirical showcase of our model rendering the code review at Microsoft, (2) validate our model in comparison with an equivalent, but time-aggregated model, and, thereby, (3) demonstrate the outstanding importance of time for research on communication networks. Lastly, we discuss the implications, the practical applications, and an outlook on future research on communication networks as distributed and decentralized information repositories-unlocked by our novel model. Highlights• Communication networks are distributed, decentralized, and self-organizing information repositories.• Information diffusion is the time-dependent spread of information in such networks.• Our novel model overcomes the limitation of existing graph-based communication models.• We validate our model in a simulation of information diffusion within Microsoft's code review.• Our model opens new research directions on communication in software engineering.

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“…When it comes to adopting tools in the open-source software ecosystem Lamba et al (2020) looked at how the usage of a number of tools spread by tracking badges from the projects main page. They found that social exposure, competition, and observability affect the adoption.…”

Section: Related Workmentioning

confidence: 99%

Dependency management bots in open-source systems—prevalence and adoption

Erlenhov

Neto

Leitner

2022

PeerJ Computer Science

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Bots have become active contributors in maintaining open-source repositories. However, the definitions of bot activity in open-source software vary from a more lenient stance encompassing every non-human contributions vs frameworks that cover contributions from tools that have autonomy or human-like traits (i.e., Devbots). Understanding which of those definitions are being used is essential to enable (i) reliable sampling of bots and (ii) fair comparison of their practical impact in, e.g., developers’ productivity. This paper reports on an empirical study composed of both quantitative and qualitative analysis of bot activity. By analysing those two bot definitions in an existing dataset of bot commits, we see that only 10 out of 54 listed tools (mainly dependency management) comply with the characteristics of Devbots. Moreover, five of those Devbots have similar patterns of contributions over 93 projects, such as similar proportions of merged pull-requests and days until issues are closed. Our analysis also reveals that most projects (77%) experiment with more than one bot before deciding to adopt or switch between bots. In fact, a thematic analysis of developers’ comments in those projects reveal factors driving the discussions about Devbot adoption or removal, such as the impact of the generated noise and the needed adaptation in development practices within the project.

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Heard it through the Gitvine: an empirical study of tool diffusion across the npm ecosystem

Cited by 11 publications

References 89 publications

An empirical study of emoji use in software development communication

An empirical study of emoji use in software development communication

Only Time Will Tell: Modelling Information Diffusion in Code Review with Time-Varying Hypergraphs

Dependency management bots in open-source systems—prevalence and adoption

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