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PullReq-CI

<p>Software processes comprise many steps; coding is followed by building, integration testing, system testing, deployment,<br> operations, among others. Software process integration and automation have been areas of key concern in software engineering,<br> ever since the pioneering work of Osterweil; market pressures for Agility, and open, decentralized, software development<br> have provided additional pressures for progress in this area. But do these innovations actually help projects?<br> Given the numerous confounding factors that can influence project performance, it can be a challenge to discern the effects<br> of process integration and automation. Software project ecosystems such as GitHub provide a new opportunity in<br> this regard: one can readily find large numbers of projects in various stages of process integration and automation, and<br> gather data on various influencing factors as well as productivity and quality outcomes. In this paper we use large,<br> historical data on process metrics and outcomes in GitHub projects to discern the e↵ects of one specific innovation in<br> process automation: continuous integration. Our main finding is that continuous integration improves the productivity<br> of project teams, who can integrate more outside contributions, without an observable diminishment in code quality.<br>  </p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

Topics

Dataset details

Repository
zenodo
Published
October 29, 2015
License
cc-by-4.0
DOI
10.5281/zenodo.581686

Scored with release 0.9.0

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