Continuous deployment of software intensive products and services: A systematic mapping study

Rodríguez, Pilar; Haghighatkhah, Alireza; Lwakatare, Lucy Ellen; Teppola, Susanna; Suomalainen, Tanja; Eskeli, Juho; Karvonen, Teemu; Kuvaja, Pasi; Verner, June M.; Oivo, Markku

doi:10.1016/j.jss.2015.12.015

Cited by 198 publications

(170 citation statements)

References 68 publications

(614 reference statements)

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“…With the increase in relevance of modern Web engineering concepts, such as continuous deployment [16] and cloud computing [17], empirical research on how to quickly build and deploy code on virtualized infrastructure has received more attention. Seminal early work on build systems has been conducted by McIntosh et al, who studied both, Java-based build systems [18] and building software more generally [19].…”

Section: Related Workmentioning

confidence: 99%

An empirical analysis of the Docker container ecosystem on GitHub

Cito

Schermann

Wittern

et al. 2017

Preprint

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Abstract-Docker allows packaging an application with its dependencies into a standardized, self-contained unit (a so-called container), which can be used for software development and to run the application on any system. Dockerfiles are declarative definitions of an environment that aim to enable reproducible builds of the container. They can often be found in source code repositories and enable the hosted software to come to life in its execution environment. We conduct an exploratory empirical study with the goal of characterizing the Docker ecosystem, prevalent quality issues, and the evolution of Dockerfiles. We base our study on a data set of over 70000 Dockerfiles, and contrast this general population with samplings that contain the Top-100 and Top-1000 most popular Docker-using projects. We find that most quality issues (28.6%) arise from missing version pinning (i.e., specifying a concrete version for dependencies). Further, we were not able to build 34% of Dockerfiles from a representative sample of 560 projects. Integrating quality checks, e.g., to issue version pinning warnings, into the container build process could result into more reproducible builds. The most popular projects change more often than the rest of the Docker population, with 5.81 revisions per year and 5 lines of code changed on average. Most changes deal with dependencies, that are currently stored in a rather unstructured manner. We propose to introduce an abstraction that, for instance, could deal with the intricacies of different package managers and could improve migration to more light-weight images.

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Section: Related Workmentioning

confidence: 99%

An empirical analysis of the Docker container ecosystem on GitHub

Cito

Schermann

Wittern

et al. 2017

Preprint

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“…The development organization wanted to develop the capacity for continuous delivery (Rodríguez et al 2016). As a step towards that goal, the organization adopted agile methods (Schwaber and Beedle 2002).…”

Section: Introductionmentioning

confidence: 99%

Large-scale agile transformation at Ericsson: a case study

et al. 2018

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Many large organizations are adopting agile software development as part of their continuous push towards higher flexibility and shorter lead times, yet few reports on large-scale agile transformations are available in the literature. In this paper we report how Ericsson introduced agile in a new R&D product development program developing a XaaS platform and a related set of services, while simultaneously scaling it up aggressively. The overarching goal for the R&D organization, distributed to five sites at two continents, was to achieve continuous feature delivery. This single case study is based on 45 semistructured interviews during visits at four sites, and five observation sessions at three sites. We describe how the organization experimented with different set-ups for their tens of agile teams aiming for rapid end-to-end development: from component-based virtual teams to totally cross-functional, cross-component, cross-site teams. Moreover, we discuss the challenges the organization faced and how they mitigated them on their journey towards continuous and rapid software engineering. We present four lessons learned for large-scale agile transformations: 1) consider using an experimental approach to transformation, 2) consider implementing the transformation step-wise in complex large-scale settings, 3) team inter-changeability can be limited in a complex large-scale product -specialization might be needed, and 4) not using a common agile framework for the whole organization, in combination with insufficient common trainings and coaching may lead to a lack of common direction in the agile implementation. Further in-depth case studies on large-scale agile transformations, on customizing agile to large-scale settings, as well as on the use of scaling frameworks are needed.

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“…As a starting point, we studied [12,15,27], which we considered standard CD literature at the time we conducted our pre-study (the mapping study described in [28], which we also consider seminal for the field, was not yet available). From those sources, we extracted practices and categorized them into five categories: automation, rollout, quality assurance, issue detection and handling, and awareness.…”

Section: Pre-studymentioning

confidence: 99%

“…Unfortunately, despite substantial recent research interest (e.g., [21,27,28]), our knowledge of CD practices outside of a number of well-known and outspoken industrial leaders remains spotty. This is concerning for two reasons.…”

Section: Introductionmentioning

confidence: 99%

An empirical study on principles and practices of continuous delivery and deployment

Schermann

Cito

Leitner

et al. 2016

Preprint

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Despite substantial recent research activity related to continuous delivery and deployment (CD), there has not yet been a systematic, empirical study on how the practices often associated with continuous deployment have found their way into the broader software industry. This raises the question to what extent our knowledge of the area is dominated by the peculiarities of a small number of industrial leaders, such as Facebook. To address this issue, we conducted a mixed-method empirical study, consisting of a pre-study on literature, qualitative interviews with 20 software developers or release engineers with heterogeneous backgrounds, and a Web-based quantitative survey that attracted 187 complete responses. A major trend in the results of our study is that architectural issues are currently one of the main barriers for CD adoption. Further, feature toggles as an implementation technique for partial rollouts lead to unwanted complexity, and require research on better abstractions and modelling techniques for runtime variability. Finally, we conclude that practitioners are in need for more principled approaches to release decision making, e.g., which features to conduct A/B tests on, or which metrics to evaluate.

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Continuous deployment of software intensive products and services: A systematic mapping study

Cited by 198 publications

References 68 publications

An empirical analysis of the Docker container ecosystem on GitHub

An empirical analysis of the Docker container ecosystem on GitHub

Large-scale agile transformation at Ericsson: a case study

An empirical study on principles and practices of continuous delivery and deployment

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