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Context: In continuous deployment, software and services are rapidly deployedto end-users using an automated deployment pipeline. Defects in infrastructureas code (IaC) scripts can hinder the reliability of the automated deploymentpipeline. We hypothesize that certain properties of IaC source code such aslines of code and hard-coded strings used as configuration values, showcorrelation with defective IaC scripts. Objective: The objective of this paperis to help practitioners in increasing the quality of infrastructure as code(IaC) scripts through an empirical study that identifies source code propertiesof defective IaC scripts. Methodology: We apply qualitative analysis ondefect-related commits mined from open source software repositories to identifysource code properties that correlate with defective IaC scripts. Next, wesurvey practitioners to assess the practitioner's agreement level with theidentified properties. We also construct defect prediction models using theidentified properties for 2,439 scripts collected from four datasets. Results:We identify 10 source code properties that correlate with defective IaCscripts. Of the identified 10 properties we observe lines of code andhard-coded string to show the strongest correlation with defective IaC scripts.Hard-coded string is the property of specifying configuration value ashard-coded string. According to our survey analysis, majority of thepractitioners show agreement for two properties: include, the property ofexecuting external modules or scripts, and hard-coded string. Using theidentified properties, our constructed defect prediction models show aprecision of 0.70~0.78, and a recall of 0.54~0.67.

Source Code Properties of Defective Infrastructure as Code Scripts