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
ScienceDex for faculty
Your academic CV and NIH biosketch
Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.