Which Factors Influence Practitioners' Usage of Build Automation Tools?
Even though build automation tools help to reduce errors and rapid releases of software changes, use of build automation tools is not widespread amongst software practitioners. Software practitioners perceive build automation tools as complex, which can hinder the adoption of these tools. How well founded such perception is, can be determined by systematic exploration of adoption factors that influence usage of build automation tools. The goal of this paper is to aid software practitioners in increasing their usage of build automation tools by identifying the adoption factors that influence usage of these tools. We conducted a survey to empirically identify the adoption factors that influence usage of build automation tools. We obtained survey responses from 268 software professionals who work at NestedApps, Red Hat, as well as contribute to open source software. We observe that adoption factors related to complexity do not have the strongest influence on usage of build automation tools. Instead, we observe compatibility-related adoption factors, such as adjustment with existing tools, and adjustment with practitioner’s existing workflow, to have influence on usage of build automation tools with greater importance. Findings from our paper suggest that usage of build automation tools might increase if: build automation tools fit well with practitioners’ existing workflow and tool usage; and usage of build automation tools are made more visible among practitioners’ peers.
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Which Factors Influence Practitioners' Usage of Build Automation Tools?
- 5. 5 Background (Contd.) • Build (B) tools: – Example: Ant and Maven. • Continuous integration (CI) tools: – Example: Jenkins and Travis-CI. • Infrastructure as Code (IaC) tools: – Example: Chef and Puppet. • Version control (VC) tools: – Example: Git and Subversion (SVN).
- 6. 6 Background (Contd.) • Education - 6 factors • Diffusion of Innovation (DOI) Theory – Advantages - 4 factors – Compatibility - 4 factors – Complexity - 4 factors – Observability - 4 factors – Trialability - 4 factors
- 7. 7 Our Contributions • A list of adoption factors that influence usage of B,CI, IaC, and VC tools; and • A rank of the identified adoption factors that influence usage of B,CI, IaC, and VC tools
- 8. 8 Research Questions • RQ-1: Which adoption factors influence usage of B,CI, IaC, and VC tools? • RQ-2: How can we prioritize the identified influencing adoption factors for B,CI, IaC, and VC tools?
- 10. 10 Empirical Findings: Summary of Professional Experience 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% B CI IaC VC < 1 y 1 ~ 2 y 3 ~ 5 y 6 ~ 10 y > 10 y
- 11. 11 Empirical Findings: Summary of Tool Usage 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% B CI IaC VC < 1 y 1 ~ 2 y 3 ~ 5 y 6 ~ 10 y > 10 y
- 12. 12 Empirical Findings: RQ1 (“Which adoption factors influence usage of B, CI, IaC, and VC tools?”) • Build tools (B) – Advantages – Compatibility – Complexity – Education – Observability
- 13. 13 Empirical Findings: RQ1 (“Which adoption factors influence usage of B, CI, IaC, and VC tools?”) • Continuous integration tools (CI) – Compatibility – Complexity – Education – Observability – Trialability
- 14. 14 Empirical Findings: RQ1 (“Which adoption factors influence usage of B, CI, IaC, and VC tools?”) • Infrastructure as code tools (IaC) – Compatibility – Education – Observability – Trialability
- 15. 15 Empirical Findings: RQ1 (“Which adoption factors influence usage of B, CI, IaC, and VC tools?”) • Version control tools (VC) – Compatibility – Complexity – Education – Observability – Trialability
- 17. 17 Empirical Findings: RQ2 (“How can we prioritize the identified influencing adoption factors for B, CI, IaC, and VC tools?”) • Summary: – For B tools, the highest priority adoption factor is ‘B tools are highly configurable’ (Compatibility). – For CI tools, the highest priority factor is ‘CI tools are compatible with the technologies that I use’ (Compatibility). – For IaC tools, the highest priority factor is ‘Use of IaC tools is not very visible in my organization’ (Observability). – For VC tools, the factor ‘fits well with the way I work’ (Compatibility) – Overall, Education-related adoption factors have lower priority.
- 18. 18 Implications • Select build automation tools that fit well with the usual work style of the team members and that can be easily customized to the needs of the team members – Example: A team that uses Ruby might adopt tools that are Ruby-friendly e.g. Chef as a IaC tool, and Rake as a B tool.
- 20. 20 Limitations • Survey response rate: 9.9% • Factors used in the survey: 26 adoption factors • Factor selection process: Subjectivity
- 21. 21 Conclusion • Survey of 268 software professionals. • Compatibility of build automation tools can increase usage. • Observability of build automation tool usage can increase usage.