A grounded theory analysis of modern web applications

Bang, Soon K.; Chung, Sam; Choh, Young; Dupuis, Marc

doi:10.1145/2512209.2512229

Cited by 44 publications

(32 citation statements)

References 3 publications

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“…There is substantial interest in practices for achieving continuous delivery and rapid, robust deployment goals [1], [2], [3]. However, we suggest there is a need to focus on more than practices.…”

Section: Introductionmentioning

confidence: 99%

Toward Design Decisions to Enable Deployability: Empirical Study of Three Projects Reaching for the Continuous Delivery Holy Grail

Bellomo

Ernst

Nord

et al. 2014

2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks

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There is growing interest in continuous delivery practices to enable rapid and reliable deployment. While practices are important, we suggest architectural design decisions are equally important for projects to achieve goals such continuous integration (CI) build, automated testing and reduced deployment-cycle time. Architectural design decisions that conflict with deployability goals can impede the team's ability to achieve the desired state of deployment and may result in substantial technical debt. To explore this assertion, we interviewed three project teams striving to practicing continuous delivery. In this paper, we summarize examples of the deployability goals for each project as well as the architectural decisions that they have made to enable deployability. We present the deployability goals, design decisions, and deployability tactics collected and summarize the design tactics derived from the interviews in the form of an initial draft version hierarchical deployability tactic tree.

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Section: Introductionmentioning

confidence: 99%

Toward Design Decisions to Enable Deployability: Empirical Study of Three Projects Reaching for the Continuous Delivery Holy Grail

Bellomo

Ernst

Nord

et al. 2014

2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks

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show abstract

“…We applied Summative Content Analysis (SCA) and Directed Content Analysis (DCA) respectively [30] are to inductively analyze qualitative data from job advertisements. Major and minor categories of KSCs were later developed in accordance with the two sources from the literature [31,32].…”

Section: A Research Designmentioning

confidence: 99%

“…From this document 69 individual job [31]. The final categories used to capture key words and concepts were Knowledge Area, Technology and Tools, Programming Languages, Methodology and Capabilities.…”

Section: C) Data Processingmentioning

confidence: 99%

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Emerging Trends for Global DevOps: A New Zealand Perspective

Hussain

Clear

MacDonell

2017

2017 IEEE 12th International Conference on Global Software Engineering (ICGSE)

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Abstract-The DevOps phenomenon is gaining popularity through its ability to support continuous value delivery and ready accommodation of change. However, given the relative immaturity and general confusion about DevOps, a common view of expectations from a DevOps role is lacking. Through investigation of online job advertisements, combined with interviews, we identified key Knowledge Areas, Skills and Capabilities for a DevOps role and their relative importance in New Zealand's job market. Our analysis also revealed the global dimensions and the emerging nature of the DevOps role in GSE projects. This research adds a small advanced economy (New Zealand) perspective to the literature on DevOps job advertisements and should be of value to employers, job seekers, researchers as well educators and policy makers.

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“…By applying a qualitative analysis approach, Bang et al [4] investigated the supporting way of factors, like knowledge, skills and abilities, for DevOps. Lwakatare [5] identified four main dimensions of DevOps: collaboration, automation, measurement and monitoring.…”

Section: A Academic Researchmentioning

confidence: 99%

Exploring DevOps for Data Analytical System with Essential Demands Elicitation

Zheng

Liu

Lin³

2016

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-DevOps is an emerging concept and methodology for bridging the gap in the process of software development. At present, applying DevOps to data analytical system (DAS) is increasingly embraced. But the characteristics of this system, such as data protection, always leads to a series of constrains. It's a bit difficult to conduct DevOps on data analytical system. Moreover, there are no DevOps solutions for reference. Therefore, exploring DevOps for data analytical system is valuable.In this paper, we illustrate DevOps demands of data analytical system from different perspectives, and constantly emphasize the importance of automation toolchain. Based on them, a process model for DAS DevOps (D 2 Ops) is proposed to clarify participants activities. In order to improve the efficiency, we attempt to integrate the automation toolchain. With the consideration of stability, six generic process components are designed to support this model. They can be the selection criteria for specific automation tools. We also present a reference facility based on these generic process components, and illustrate its implementation combing with a practical case.

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A grounded theory analysis of modern web applications

Cited by 44 publications

References 3 publications

Toward Design Decisions to Enable Deployability: Empirical Study of Three Projects Reaching for the Continuous Delivery Holy Grail

Toward Design Decisions to Enable Deployability: Empirical Study of Three Projects Reaching for the Continuous Delivery Holy Grail

Emerging Trends for Global DevOps: A New Zealand Perspective

Exploring DevOps for Data Analytical System with Essential Demands Elicitation

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