Gang of eight: a defect taxonomy for infrastructure as code scripts
Reviewed by Greg Wilson / 2021-08-26
Keywords: Design Patterns, DevOps
I enjoyed Rahman2020a for two reasons. The first is the taxonomy the authors develop: cataloging the ways that infrastructure scripts go wrong is a necessary first step toward building tools that prevent or detect those errors, and if developers and admins could sanity check changes to deployment scripts, they'd get more sleep.
The second reason I liked this paper is that its pragmatic mix of qualitative and quantitative methods is more powerful than either approach on its own. The authors looked at over 1400 detect-related commits to identify categories, surveyed 66 practitioners to check that their categorization made sense, then analyze over 80,000 commits from almost 300 projects to see how common these mistakes are.
So what errors did they identify?
- Conditional errors (i.e., a logical error leads to executing the wrong branch in a script)
- Erroneous configuration data (I once set a timeout to 07 seconds instead of 70 seconds and spent three days trying to track down the problem)
- Missing or incorrect dependencies
- Incorrect documentation ("We did exactly what the comments told us to do, but the comments were wrong")
- Security, such as confidential data showing up in logs
- Idempotency, meaning that executing the script multiple times doesn't have the same effect as executing it only once
I don't know if it's possible to automate checks for all of these problems, but having them in a checklist or a training course would help a lot of developers.
Rahman2020a Akond Rahman, Effat Farhana, Chris Parnin, and Laurie Williams: "Gang of eight: a defect taxonomy for infrastructure as code scripts". Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, 10.1145/3377811.3380409.
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 may help in advancing the science of IaC script quality.