Gang of Eight: A Defect Taxonomy for Infrastructure as Code Scripts
Defects in infrastructure as code (IaC) scripts can have serious consequences, for example, creating large-scale system outages. A taxonomy of IaC defects can be useful for understanding the nature of defects, and identifying activities needed to fix and prevent defects in IaC scripts. The goal of this paper is to help practitioners improve the quality of infrastructure as code (IaC) scripts by developing a defect taxonomy for IaC scripts through qualitative analysis. We develop a taxonomy of IaC defects by applying qualitative analysis on 1,448 defect-related commits collected from open source software (OSS) repositories of the Openstack organization. We conduct a survey with 66 practitioners to assess if they agree with the identified defect categories included in our taxonomy. We quantify the frequency of identified defect categories by analyzing 80,425 commits collected from 291 OSS repositories spanning across 2005 to 2019.
Our defect taxonomy for IaC consists of eight categories, including a category specific to IaC called idempotency (i.e., defects that lead to incorrect system provisioning when the same IaC script is executed multiple times). We observe the surveyed 66 practitioners to agree most with idempotency. The most frequent defect category is configuration data i.e., providing erroneous configuration data in IaC scripts. Our taxonomy and the quantified frequency of the defect categories can help practitioners to improve IaC script quality by prioritizing verification and validation efforts.
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Haijun WangAnt Financial Services Group, China; CSSE, Shenzhen University, China, Xiaofei XieNanyang Technological University, Yi LiNanyang Technological University, Cheng WenShenzhen University, Yuekang LiNanyang Technological University, Yang LiuNanyang Technological University, Singapore, Shengchao QinUniversity of Teesside, Hongxu ChenResearch Associate, Yulei SuiUniversity of Technology Sydney, AustraliaLink to publication DOI Pre-print
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Akond RahmanTennessee Tech University, Effat FarhanaNorth Carolina State University, Chris ParninNorth Carolina State University, Laurie WilliamsNorth Carolina State UniversityPre-print
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