An exploratory study of reactions to bot comments on GitHub

Farah, Juan Carlos; Spaenlehauer, Basile; Lu, Xianju; Ingram, Sandy; Gillet, Denis

doi:10.1145/3528228.3528409

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…However, projects should be aware that the rule-based nature of Stale bot could wrongly close PRs that may still be under progress despite being inactive for some time [63]. Moreover, the automatic closure of PRs by Stale bot is known to raise the most negative reactions from the contributors and participants, especially when they perceive the closure as erroneous or unjustified [7].…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, they concluded that setting up and using Stale bot does not require much effort from the projects. Several studies [7,38,47,63,66] have also incidentally mentioned that Stale bot introduces noise and friction for both the contributors and the maintainers. Reasons and Consequences of PR Abandonment.…”

Section: Related Workmentioning

confidence: 99%

“…To deal with abandoned PRs, Stale bot was released in 2017 to automatically triage abandoned issues and PRs and is adopted by many open-source projects [66,67,68]. However, studies [69,70,71,72,73] have mentioned that Stale bot introduces noise and friction for both the contributors and the maintainers. Khatoonabadi et al [10] conducted an empirical study to understand the helpfulness of Stale bot in the context of pull-based development.…”

Section: Studies Onmentioning

confidence: 99%

“…They argue that while Stale bot may initially seem helpful, it results in duplicated PRs, fragmented information, and eventually frustration in the community. Some studies have also incidentally mentioned that Stale bot can introduce noise and friction for both the contributors and the maintainers [7,38,47,63,66].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests–A Mixed-Methods Study of 10 Large Open-Source Projects

Khatoonabadi

Costa

Shihab

2023

ACM Trans. Softw. Eng. Methodol.

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Pull-based development has enabled numerous volunteers to contribute to open-source projects with fewer barriers. Nevertheless, a considerable amount of pull requests (PRs) with valid contributions are abandoned by their contributors , wasting the effort and time put in by both the contributors and maintainers. To better understand the underlying dynamics of contributor-abandoned PRs, we conduct a mixed-methods study using both quantitative and qualitative methods. We curate a dataset consisting of 265,325 PRs including 4,450 abandoned ones from ten popular and mature GitHub projects and measure 16 features characterizing PRs, contributors, review processes, and projects. Using statistical and machine learning techniques, we find that complex PRs, novice contributors, and lengthy reviews have a higher probability of abandonment and the rate of PR abandonment fluctuates alongside the projects’ maturity or workload. To identify why contributors abandon their PRs, we also manually examine a random sample of 354 abandoned PRs. We observe that the most frequent abandonment reasons are related to the obstacles faced by contributors, followed by the hurdles imposed by maintainers during the review process. Finally, we survey the top core maintainers of the studied projects to understand their perspectives on dealing with PR abandonment and on our findings.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Studies Onmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests–A Mixed-Methods Study of 10 Large Open-Source Projects

Khatoonabadi

Costa

Shihab

2023

ACM Trans. Softw. Eng. Methodol.

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“…Taking into account laughter user's production might therefore be a valuable piece of information to be integrated in SDS, being a potential indicator to support failure detection: when not expected indeed, laughter from the user might signal that the generated behaviour or utterance has been appraised as incongruous by the user in relation with the contextual interaction. Some exploratory work in this direction is being conducted in the context of chat bot interactions, analysing the occurrence of laughter reaction to the automatically generated messages [30].…”

Section: Failure Detection and Failure Managementmentioning

confidence: 99%

Laughter Meaning Construction and Use in Development: Children and Spoken Dialogue Systems

Mazzocconi

2022

HCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments

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In the current work a brief overview of some studies conducted on laughter taking a multidisciplinary perspective will be presented. The integration of analyses of corpus data, theoretical and formal insights, behavioural experiments, machine learning methods, and developmental data, turned out to be fruitful to gain insight into laughter behaviour and on how its production contributes to our conversations. A crucial claim emerging from the studies presented is that laughter conveys propositional meaning interacting with other modalities, in a manner akin to other content bearing words. The implications that such results have for the implementations of more competent, from a semantic and pragmatic perspective, spoken dialogue systems will be outlined. Especially the qualitative and quantitative analysis of developmental data will offer the basis for the proposal of some specific applications.

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A Control Room Monitored Software Engineering Robot Working Fully Autonomously at High Speed

Florczyk

2023

2023 International Conference on Electrical, Computer and Energy Technologies (ICECET)

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An exploratory study of reactions to bot comments on GitHub

Cited by 6 publications

References 21 publications

On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests–A Mixed-Methods Study of 10 Large Open-Source Projects

On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests–A Mixed-Methods Study of 10 Large Open-Source Projects

Laughter Meaning Construction and Use in Development: Children and Spoken Dialogue Systems

A Control Room Monitored Software Engineering Robot Working Fully Autonomously at High Speed

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