Infrastructure as code (IaC) scripts, such as Ansible scripts, are used to provision computing infrastructure at scale. Existence of bugs in IaC test scripts, such as, configuration and security bugs, can be consequential for the provisioned computing infrastructure. A characterization study of bugs in IaC test scripts is the first step to understand the quality concerns that arise during testing of IaC scripts, and also provide recommendations for practitioners on quality assurance. We conduct an empirical study with 4,831 Ansible test scripts mined from 104 open source software (OSS) repositories where we quantify bug frequency, and categorize bugs in test scripts. We further categorize testing patterns, i.e., recurring coding patterns in test scripts, which also correlate with appearance of bugs. From our empirical study, we observe 1.8% of 4,831 Ansible test scripts to include a bug, and 45.2% of the 104 repositories to contain at least one test script that includes bugs. We identify 7 categories of bugs, which includes security bugs and performance bugs that are related with metadata extraction. We also identify 3 testing patterns that correlate with appearance of bugs: 'assertion roulette’, 'local only testing’, and 'remote mystery guest‘. Based on our findings, we advocate for detection and mitigation of the 3 testing patterns as these patterns can have negative implications for troubleshooting failures, reproducible deployments of software, and provisioning of computing infrastructure.
more »
« less
Evaluating the Quality of Open Source Ansible Playbooks: An Executability Perspective
Infrastructure as code (IaC) is the practice of automatically managing computing platforms, such as Internet of Things (IoT) platforms. IaC has gained popularity in recent years, yielding a plethora of software artifacts, such as Ansible playbooks that are available on social coding platforms. Despite the availability of open source software (OSS) Ansible playbooks, there is a lack of empirical research on the quality of these playbooks, which can hinder the progress of IaC-related research. To that end, we conduct an empirical study with 2,952 OSS Ansible playbooks where we evaluate the quality of OSS playbooks from the perspective of executability, i.e., if publicly available OSS Ansible playbooks can be executed without failures. From our empirical study, we observe 71.5\% of the mined 2,952 Ansible playbooks cannot be executed as is because of four categories of failures.
more »
« less
- PAR ID:
- 10540427
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400706721
- Page Range / eLocation ID:
- 2 to 5
- Subject(s) / Keyword(s):
- Ansible data quality devops executability infrastructure as code
- Format(s):
- Medium: X
- Location:
- Porto de Galinhas Brazil
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Infrastructure as code (IaC) is the practice of automatically managing computing infrastructure at scale. Despite yielding multiple benefits for organizations, the practice of IaC is susceptible to quality concerns, which can lead to large-scale consequences. While researchers have studied quality concerns in IaC manifests, quality aspects of infrastructure orchestrators, i.e., tools that implement the practice of IaC, remain an under-explored area. A systematic investigation of defects in infrastructure orchestrators can help foster further research in the domain of IaC. From our empirical study with 22,445 commits mined from the Ansible infrastructure orchestrator we observe (i) a defect density of 17.9 per KLOC, (ii) 12 categories of Ansible components for which defects appear, and (iii) the ‘Module’ component to include more defects than the other 11 components. Based on our empirical study, we provide recommendations for researchers to conduct future research to enhance the quality of infrastructure orchestrators.more » « less
-
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.more » « less
-
null (Ed.)Context: Security smells are recurring coding patterns that are indicative of security weakness and require further inspection. As infrastructure as code (IaC) scripts, such as Ansible and Chef scripts, are used to provision cloud-based servers and systems at scale, security smells in IaC scripts could be used to enable malicious users to exploit vulnerabilities in the provisioned systems. Goal: The goal of this article is to help practitioners avoid insecure coding practices while developing infrastructure as code scripts through an empirical study of security smells in Ansible and Chef scripts. Methodology: We conduct a replication study where we apply qualitative analysis with 1,956 IaC scripts to identify security smells for IaC scripts written in two languages: Ansible and Chef. We construct a static analysis tool called Security Linter for Ansible and Chef scripts (SLAC) to automatically identify security smells in 50,323 scripts collected from 813 open source software repositories. We also submit bug reports for 1,000 randomly selected smell occurrences. Results: We identify two security smells not reported in prior work: missing default in case statement and no integrity check. By applying SLAC we identify 46,600 occurrences of security smells that include 7,849 hard-coded passwords. We observe agreement for 65 of the responded 94 bug reports, which suggests the relevance of security smells for Ansible and Chef scripts amongst practitioners. Conclusion: We observe security smells to be prevalent in Ansible and Chef scripts, similarly to that of the Puppet scripts. We recommend practitioners to rigorously inspect the presence of the identified security smells in Ansible and Chef scripts using (i) code review, and (ii) static analysis tools.more » « less
-
The practice of infrastructure as code (IaC) recommends automated management of computing infrastructure with application of quality assurance, such as linting and testing. To that end, researchers recently have investigated quality concerns in IaC test manifests by deriving a catalog of test smells. The relevance of the identified smells need to be quantified by obtaining feedback from practitioners. Such feedback can help the IaC community understand if smells have relevance amongst practitioners, and derive future research directions. We survey 30 practitioners to assess the relevance of three Ansible test smell categories namely, assertion roulette, local only testing, and remote mystery guest. We observe local only testing to be the most agreed upon test smell category, whereas, assertion roulette is the least agreed upon test smell category. Our findings provide a nuanced perspective of test smells for IaC, and lays the groundwork for future research.more » « less
An official website of the United States government

