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Audiovisual . 2020
License: CC BY
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ZENODO
Audiovisual . 2020
License: CC BY
Data sources: Datacite
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A storm of relevant project-related terms to support newcomers' onboarding

Authors: Lima, Márcia; Oliveira, Edson; Tayana Conte; Gadelha, Bruno;

A storm of relevant project-related terms to support newcomers' onboarding

Abstract

Both distributed and collocated software teams use collaborative communication channels, such as instant messaging (IM) tools, to support software development and management tasks. Furthermore, when teams use IM tools, relevant software-related discussions end up stored in these tools' log files. This research aims to investigate how we can extract and use projects' knowledge from developers' IM logs to support newcomers' onboarding. We propose an approach based on data-mining techniques to automatically obtain frequent software-related discussions from the developer's IM logs, extracting what we call the Project's Frequent Knowledge (PFK). We assessed the proposed approach evaluating three newcomers' knowledge acquisition regarding a software project. The results demonstrated that, on average, 70% of the frequent software-related discussions identified in this study were useful to determine the PFK, and newcomers were able to comprehend software related issues by analyzing the PFK. Our findings indicate the usefulness of the proposed approach to extract software knowledge from developers' IM logs and support newcomers' onboarding. Moreover, a conducted follow-up interview involving newcomers and the team's project manager revealed the feasibility of using PFK on knowledge transfer and acquisition.

Keywords

Software Knowledge, Communication Tools, Newcomer Members, Data-mining

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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