Do faster releases improve software quality? An empirical case study of Mozilla Firefox

Khomh,; Dhaliwal,; Zou,; Adams, Bram

doi:10.1109/msr.2012.6224279

Cited by 98 publications

(81 citation statements)

References 10 publications

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“…In other release models (e.g., release trains [24], as used by the Firefox project), new features are rolled out according to a defined release plan. If a new feature is not ready in time for a feature cut-off date, it is delayed to the next release, which may in the worst case take months.…”

Section: Continuous Deliverymentioning

confidence: 99%

Runtime metric meets developer - Building better cloud applications using feedback

Cito

Leitner

Gall

et al. 2015

Preprint

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A unifying theme of many ongoing trends in software engineering is a blurring of the boundaries between building and operating software products. In this paper, we explore what we consider to be the logical next step in this succession: integrating runtime monitoring data from production deployments of the software into the tools developers utilize in their daily workflows (i.e., IDEs) to enable tighter feedback loops. We refer to this notion as feedback-driven development (FDD).This more abstract FDD concept can be instantiated in various ways, ranging from IDE plugins that implement feedback-driven refactoring and code optimization to plugins that predict performance and cost implications of code changes prior to even deploying the new version of the software. We demonstrate existing proof-of-concept realizations of these ideas and illustrate our vision of the future of FDD and cloud-based software development in general. Further, we discuss the major challenges that need to be solved before FDD can achieve mainstream adoption.

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Section: Continuous Deliverymentioning

confidence: 99%

Runtime metric meets developer - Building better cloud applications using feedback

Cito

Leitner

Gall

et al. 2015

Preprint

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“…Khomh et al [10] studied the impact of release frequencies on software quality, one of the observations was that with shorter release cycles users do not experience more post-deployment bugs. Mäntylä et al [11] analyzed the impact on software testing efforts when reducing the release cycle time in a case study of Mozilla Firefox.…”

Section: Related Workmentioning

confidence: 99%

Towards quality gates in continuous delivery and deployment

Schermann

Cito

Leitner

et al. 2016

2016 IEEE 24th International Conference on Program Comprehension (ICPC)

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Quality gates, steps required to ensure the reliability of code changes, are supposed to increase the confidence stakeholders have in a release. In today's fast paced environments, we have less time to perform the necessary precautions to minimize the risk of a faulty release. This leads to an inherent trade-off between risk of lower release quality and time to market. We provide a model for this tradeoff of release confidence and velocity that led to the formulation of 4 categories (cautious, balanced, problematic, madness), in which companies can be classified in. We showcase real examples of these categories as case studies based on previous empirical studies. We close by presenting possible transitions between categories that guide future research. Towards Quality Gates in Continuous Delivery and DeploymentGerald Schermann, Jürgen Cito, Philipp Leitner, and Harald C. Gall University of Zurich, Department of Informatics, Switzerland {schermann, cito, leitner, gall}@ifi.uzh.chAbstract-Quality gates, steps required to ensure the reliability of code changes, are supposed to increase the confidence stakeholders have in a release. In today's fast paced environments, we have less time to perform the necessary precautions to minimize the risk of a faulty release. This leads to an inherent trade-off between risk of lower release quality and time to market. We provide a model for this trade-off of release "confidence" and "velocity" that led to the formulation of 4 categories (cautious, balanced, problematic, madness), in which companies can be classified in. We showcase real examples of these categories as case studies based on previous empirical studies. We close by presenting possible transitions between categories that guide future research.

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“…This was for example the case for Apache (cited 2 times) and Mozilla (mentioned once). Both Apache [49,4] and Mozilla [36] are popular subjects of ecosystems research.…”

Section: Examples Of Software Ecosystemsmentioning

confidence: 99%

Challenges in Software Ecosystems Research

Serebrenik

Mens

2015

Proceedings of the 2015 European Conference on Software Architecture Workshops

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The paper is a meta-analysis of the research field of software ecosystems, by method of surveying 26 authors in the field. It presents a relevant list of literature and six themes in which challenges for software ecosystems can be grouped: Architecture and Design, Governance, Dynamics and Evolution, Data Analytics, Domain-Specific Ecosystems Solutions, and Ecosystems Analysis. As such, it provides a roadmap for future research in the field. Categories and Subject Descriptors

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Do faster releases improve software quality? An empirical case study of Mozilla Firefox

Cited by 98 publications

References 10 publications

Runtime metric meets developer - Building better cloud applications using feedback

Runtime metric meets developer - Building better cloud applications using feedback

Towards quality gates in continuous delivery and deployment

Challenges in Software Ecosystems Research

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