Marco Ortu
ABSTRACT
Automatic and repeatable builds are an established software engineering practices for achieving continuous integration and continuous delivery processes. The building phase of modern software systems is an important part of the development process such that dedicated roles as "Release Engineer" are more and more required. Software development is a collaborative activity, and when multiple developers work on the same project, they will be changing a shared master development branch at overlapping intervals. This overlap occurs because developers create parallel branches for working and then merge these branches when features are completed. Continuous integration, CI, is a workflow strategy which helps ensure everyoneâĂŹs changes will integrate with the current version of the project. This activity allows developers to catch bugs and reduce merge conflicts. Improving the building process leads to higher productivity and therefore shorter time to market, but understanding or measuring such a delicate phase is a big challenge. Open Source Communities provide valuable empirical data such as GitHub an Travis CI. These repositories represent a golden mine containing important data which can help researchers understanding the process behind the manufacturing of a software artifact. By analyzing Travis CI logs, we can directly connect a particular build with the development process behind it, not only regarding code changes but also regarding human activities, such as discussions about the implementation of a specific feature or bug resolution. Thanks to this information we can analyze the social activities of the build process enabling us to apply the same approach used for the development process.
- M. Beller, G. Gousios, and A. Zaidman. Travistorrent: Synthesizing travis ci and github for full-stack research on continuous integration. In Proceedings of the 14th working conference on mining software repositories, 2017. Google Scholar
Digital Library
- G. Destefanis, M. Ortu, S. Counsell, S. Swift, R. Tonelli, and M. Marchesi. On the randomness and seasonality of affective metrics for software development. In Proceedings of the Symposium on Applied Computing, pages 1266--1271. ACM, 2017. Google ScholarDigital Library
- G. Gousios. The ghtorrent dataset and tool suite. In Proceedings of the 10th Working Conference on Mining Software Repositories, MSR '13, pages 233--236, Piscataway, NJ, USA, 2013. IEEE Press. Google ScholarDigital Library
- S. Kim, T. Zimmermann, E. J. Whitehead Jr, and A. Zeller. Predicting faults from cached history. In Proceedings of the 29th international conference on Software Engineering, pages 489--498. IEEE Computer Society, 2007. Google ScholarDigital Library
- A. Murgia, M. Ortu, P. Tourani, B. Adams, and S. Demeyer. An exploratory qualitative and quantitative analysis of emotions in issue report comments of open source systems. Empirical Software Engineering, pages 1--44, 2017. Google ScholarDigital Library
- M. Ortu, G. Destefanis, S. Counsell, S. Swift, R. Tonelli, and M. Marchesi. Arsonists or firefighters? affectiveness in agile software development. In International Conference on Agile Software Development, pages 144--155. Springer, 2016.Google ScholarCross Ref
- M. Ortu, G. Destefanis, S. Counsell, S. Swift, R. Tonelli, and M. Marchesi. How diverse is your team? investigating gender and nationality diversity in github teams. Journal of Software Engineering Research and Development, 5(1):9, 2017.Google ScholarCross Ref
- M. Ortu, G. Destefanis, M. Kassab, S. Counsell, M. Marchesi, and R. Tonelli. Would you mind fixing this issue? an empirical analysis of politeness and attractiveness in software developed using agile boards. In Agile Processes, in Software Engineering, and Extreme Programming, pages 129--140. Springer, 2015.Google Scholar
- H. Zhang, L. Gong, and S. Versteeg. Predicting bug-fixing time: an empirical study of commercial software projects. In Proceedings of the 2013 international conference on software engineering, pages 1042--1051. IEEE Press, 2013. Google ScholarDigital Library
Index Terms
- Angry-builds: an empirical study of affect metrics and builds success on github ecosystem
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