Polyglot Code Smell Detection for Infrastructure as Code with GLITCH

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Saavedra, N (Author) Other; Gonçalves, J (Author) Other; Henriques, M (Author) Other; Ferreira, JF (Author) Other; Mendes, A (Author) FEUP

Conference proceedings International

Title: 2023 38TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING, ASE

Pages: 2042-2045

38th IEEE/ACM International Conference on Automated Software Engineering (ASE)

Echternach, LUXEMBOURG, SEP 11-15, 2023

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Other information

Authenticus ID: P-00Z-FNW

DOI: 10.1109/ase56229.2023.00162

Abstract (EN): This paper presents GLITCH, a new technology-agnostic framework that enables automated polyglot code smell detection for Infrastructure as Code scripts. GLITCH uses an intermediate representation on which different code smell detectors can be defined. It currently supports the detection of nine security smells and nine design & implementation smells in scripts written in Ansible, Chef, Docker, Puppet, or Terraform. Studies conducted with GLITCH not only show that GLITCH can reduce the effort of writing code smell analyses for multiple IaC technologies, but also that it has higher precision and recall than current state-of-the-art tools. A video describing and demonstrating GLITCH is available at: https://youtu.be/E4RhCcZjWbk.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4