Toward a catalog of software quality metrics for infrastructure code
Abstract Infrastructure-as-code (IaC) is a practice to implement continuous deployment by allowing management and provisioning of infrastructure through the definition of machine-readable files and automation around them, rather than physical hardware configuration or interactive configuration tools. On the one hand, although IaC represents an ever-increasing widely adopted practice nowadays, still little is known concerning how to best maintain, speedily evolve, and continuously improve the code behind the IaC practice in a measurable fashion. On the other hand, source code measurements are o... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2020 |
Schlagwörter: | H2020 / Netherlands / Swiss National Science Foundation / SNSF / EC / Careers / Research and Innovation action / Ambizione / European Commission / Hardware and Architecture / Information Systems / Software |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27200754 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://www.openaccessrepository.it/record/86195 |
Abstract Infrastructure-as-code (IaC) is a practice to implement continuous deployment by allowing management and provisioning of infrastructure through the definition of machine-readable files and automation around them, rather than physical hardware configuration or interactive configuration tools. On the one hand, although IaC represents an ever-increasing widely adopted practice nowadays, still little is known concerning how to best maintain, speedily evolve, and continuously improve the code behind the IaC practice in a measurable fashion. On the other hand, source code measurements are often computed and analyzed to evaluate the different quality aspects of the software developed. However, unlike general-purpose programming languages (GPLs), IaC scripts use domain-specific languages, and metrics used for GPLs may not be applicable for IaC scripts. This article proposes a catalog consisting of 46 metrics to identify IaC properties focusing on Ansible, one of the most popular IaC language to date, and shows how they can be used to analyze IaC scripts.