Towards a Taxonomy of Infrastructure as Code Misconfigurations: An Ansible Study DOI
Rohollah Nasiri, Indika Kumara, Damian A. Tamburri

et al.

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 83 - 103

Published: Oct. 18, 2024

Language: Английский

Test-suite-guided discovery of least privilege for cloud infrastructure as code DOI
Ryo Shimizu,

Yuna Nunomura,

Hideyuki Kanuka

et al.

Automated Software Engineering, Journal Year: 2024, Volume and Issue: 31(1)

Published: March 5, 2024

Language: Английский

Citations

0
Practitioners' Expectations on Code Smell Detection DOI
Zexian Zhang, Shuang Yin,

Wenliu Wei

et al.

2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), Journal Year: 2024, Volume and Issue: unknown, P. 1324 - 1333

Published: July 2, 2024

Language: Английский

Citations

0
When Your Infrastructure Is a Buggy Program: Understanding Faults in Infrastructure as Code Ecosystems DOI Open Access
Georgios-Petros Drosos, Thodoris Sotiropoulos, Georgios Alexopoulos

et al.

Proceedings of the ACM on Programming Languages, Journal Year: 2024, Volume and Issue: 8(OOPSLA2), P. 2490 - 2520

Published: Oct. 8, 2024

Modern applications have become increasingly complex and their manual installation configuration is no longer practical. Instead, IT organizations heavily rely on Infrastructure as Code (IaC) technologies, to automate the provisioning, configuration, maintenance of computing infrastructures systems. IaC systems typically offer declarative, domain-specific languages (DSLs) that allow system administrators developers write high-level programs specify desired state infrastructure in a reliable, predictable, documented fashion. Just like traditional programs, software not immune faults, with issues ranging from deployment failures critical misconfigurations often impact production used by millions end users. Surprisingly, despite its crucial role global management, tooling techniques for ensuring reliability still room improvement. In this work, we conduct comprehensive analysis 360 bugs identified within prominent ecosystems including Ansible, Puppet, Chef. Our work first in-depth exploration bug characteristics these widely-used environments. Through our aim understand: (1) how manifest, (2) underlying root causes, (3) reproduction requirements terms (e.g., operating versions) or input characteristics, (4) are fixed. Based findings, evaluate state-of-the-art reliability, identify limitations, provide set recommendations future research. We believe study helps researchers better understand complexity peculiarities software, develop advanced more reliable robust configurations.

Language: Английский

Citations

0
Towards a Taxonomy of Infrastructure as Code Misconfigurations: An Ansible Study DOI
Rohollah Nasiri, Indika Kumara, Damian A. Tamburri

et al.

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 83 - 103

Published: Oct. 18, 2024

Language: Английский

Citations

0