Where Are The Gaps? A Systematic Mapping Study of Infrastructure as Code Research
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Abstract (arXiv)
Context:Infrastructure as code (IaC) is the practice to automatically configure system dependencies and to provision local and remote instances. Practitioners consider IaC as a fundamental pillar to implement DevOps practices, which helps them to rapidly deliver software and services to end-users. Information technology (IT) organizations, such as Github, Mozilla, Facebook, Google and Netflix have adopted IaC. A systematic mapping study on existing IaC research can help researchers to identify potential research areas related to IaC, for example, the areas of defects and security flaws that may occur in IaC scripts. Objective: The objective of this paper is to help researchers identify research areas related to infrastructure as code (IaC) by conducting a systematic mapping study of IaC-related research. Methodology: We conduct our research study by searching six scholar databases. We collect a set of 33,887 publications by using seven search strings. By systematically applying inclusion and exclusion criteria, we identify 31 publications related to IaC. We identify topics addressed in these publications by applying qualitative analysis. Results: We identify four topics studied in IaC-related publications: (i) framework/tool for infrastructure as code; (ii) use of infrastructure as code; (iii) empirical study related to infrastructure as code; and (iv) testing in infrastructure as code. According to our analysis, 52% of the studied 31 publications propose a framework or tool to implement the practice of IaC or extend the functionality of an existing IaC tool. Conclusion: As defects and security flaws can have serious consequences for the deployment and development environments in DevOps, along with other topics, we observe the need for research studies that will study defects and security flaws for IaC.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jul 2018.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 2; 2026: 4.
9 papers.
- 2024A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directionscited by 25
- 2025Multi-Agent Code-Orchestrated Generation for Reliable Infrastructure-as-Codecited by 5
- 2025AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compressioncited by 2
- 2026RIVA: Leveraging LLM Agents for Reliable Configuration Drift Detectioncited by 1
- 2023Optimizing IaC Configurations: a Case Study Using Nature-inspired Computingcited by 0
- 2024Multiobjective Optimization Analysis for Finding Infrastructure-as-Code Deployment Configurationscited by 0
- 2026IntelliSA: An Intelligent Static Analyzer for IaC Security Smell Detection Using Symbolic Rules and Neural Inferencecited by 0
- 2026Agyn: An Open-Source Platform for AI Agents with Scalable On-Demand Execution, Agent Definition as a Code, and Zero-Trust Accesscited by 0
- 2026Compared to What? A Human-Anchored Security Benchmark for LLM-Generated Infrastructure-as-Codecited by 0
- 2026Compared to What? A Human-Anchored Security Benchmark for LLM-Generated Infrastructure-as-Code28 Aug 2026
- 2026Agyn: An Open-Source Platform for AI Agents with Scalable On-Demand Execution, Agent Definition as a Code, and Zero-Trust Access26 May 2026
- 2026RIVA: Leveraging LLM Agents for Reliable Configuration Drift Detection2 Mar 2026
- 2026IntelliSA: An Intelligent Static Analyzer for IaC Security Smell Detection Using Symbolic Rules and Neural Inference21 Jan 2026
- 2025AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression15 Dec 2025
- 2025Multi-Agent Code-Orchestrated Generation for Reliable Infrastructure-as-Code4 Oct 2025
- 2024A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions16 Dec 2024
- 2024Multiobjective Optimization Analysis for Finding Infrastructure-as-Code Deployment Configurations18 Jan 2024
- 2023Optimizing IaC Configurations: a Case Study Using Nature-inspired Computing15 Nov 2023