IAC2: Infrastructure-as-code Architecture Decision Compliance

架构即代码（IaC）可帮助从业人员自动配置和管理大规模的IT基础架构，而不是使用手动流程。IaC的承诺是简单、快速、安全、可靠和可重复的IT基础设施配置和管理。在IaC设计和开发中，许多复杂的体系结构设计决策（ADD）是针对IaC系统、底层基础设施和要交付的软件系统而做出的。今天，使IaC的复杂性（通常是巨大的）可管理的基础缺失，导致IaC设计和开发的低质量，高风险和高成本/工作。该项目的目标是开发基本的概念和方法，以解决这些研究差距，通过研究以下研究问题：RQ 1：如何可以在今天的文献中记录的非正式IAC既定的做法，以严格的方式指定？RQ 2：如何以系统化和自动化的方式识别和检测广泛的IaC代码，特别是架构气味和模式？RQ 3：如何通过基于证据的决策来解决大规模IaC架构的巨大复杂性？为了解决研究问题，该项目旨在通过严格的IaC ADD合规规范来降低复杂性并提高质量，并通过将这些规范基于既定模式和难闻气味来降低风险和不确定性。在此基础上，它旨在提供精确识别IaC代码和架构中这些模式和不良气味的方法，并提供IaC代码和架构中的自动检测。这些贡献将通过精确识别和自动检测来提高质量，并通过取代手动流程来降低风险和不确定性，这也减少了维护复杂IaC架构所需的成本和工作。最后，该项目旨在提供新的手段，以持续衡量和监测IaC合规性的改善和退化，从而实现基于证据的架构改进。所有项目成果都将在各种实证研究中进行评估。虽然IaC已被用作一种工具，以帮助不断改善系统的部署，例如云应用程序，IaC架构本身的演变尚未在文献中研究。考虑到IaC在实践中的广泛使用以及现有IaC架构在大型部署中的巨大复杂性，很可能会做出非最佳决策，从而导致严重的设计问题。这个问题还没有得到任何重大的研究工作，需要新的基础研究。

Infrastructure-as-code (IaC) helps practitioner to automatically provision and manage IT infrastructures at scale, rather than using manual processes. The promise of IaC is easy, rapid, secure, reliable, and repeatable IT infrastructure provisioning and management. In IaC design and development many complex architectural design decisions (ADD) are made for the IaC system, the underlying infrastructure, and the software system to be delivered. Today foundations to make the (often huge) complexity of IaC manageable are missing, leading to low quality, high risks, and high costs/efforts in IaC design and development. The project has the objective to develop foundational concepts and methods to address these research gaps by studying the following research questions:RQ1: How can the informal IaC established practices documented in the literature today be specified in a rigorous way?RQ2: How can a broad set of IaC code and especially architecture smells and patterns be identified and detected in a systematic and automated fashion?RQ3: How can the enormous complexity of large-scale IaC architectures be tackled through evidence-based decision making?To address the research questions, the project aims to reduce complexity and improve quality through rigorous IaC ADD compliance specifications, and reduce risks and uncertainties by basing these specifications on established patterns and bad smells. Based on this foundation, it aims to provide means for precise identification of these patterns and bad smells in IaC code and architectures, and to provide automatic detection in IaC code and architectures. Together these contributions will enable improving quality through precise identification and automatic detection, and reducing risks and uncertainties by replacing manual processes, which also reduces the necessary costs and efforts in especially maintaining complex IaC architectures. Finally, the project aims to provide novel means for continuously measuring and monitoring IaC compliance improvements and degradations, thus enabling evidence-based improvement of the architecture. All project results will be evaluated in various empirical studies. While IaC has been used as a tool to help continuously improve the system to be deployed, e.g. for cloud applications, the evolution of the IaC architecture itself has not yet been studied in the literature. Given the broad use of IaC in practice and the enormous complexity of existing IaC architectures in large deployments, it is rather likely that often non-optimal decisions will be made, leading to severe design issues. This problem has not been addressed by any major research effort yet and requires new foundational research.