ASE 2023 (series) / Tool Demonstrations /
Polyglot Code Smell Detection for Infrastructure as Code with GLITCH
Wed 13 Sep 2023 11:30 - 11:42 at Plenary Room 2 - Code Quality and Code Smells Chair(s): Bernd Fischer
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.
Presentation (GLITCH ASE23.pptx) | 18.88MiB |
Wed 13 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
Wed 13 Sep
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:30 - 12:00 | Code Quality and Code SmellsTool Demonstrations / Journal-first Papers / Research Papers at Plenary Room 2 Chair(s): Bernd Fischer Stellenbosch University | ||
10:30 12mTalk | Contextuality of Code Representation Learning Research Papers Yi Li New Jersey Institute of Technology, Shaohua Wang New Jersey Institute of Technology, Tien N. Nguyen University of Texas at Dallas | ||
10:42 12mTalk | On-the-fly Improving Performance of Deep Code Models via Input Denoising Research Papers Pre-print File Attached | ||
10:54 12mTalk | Using Deep Learning to Automatically Improve Code Readability Research Papers Antonio Vitale University of Molise, Italy, Valentina Piantadosi University of Molise, Simone Scalabrino University of Molise, Rocco Oliveto University of Molise Pre-print | ||
11:06 12mTalk | Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We? Research Papers Antonio Mastropaolo Università della Svizzera italiana, Massimiliano Di Penta University of Sannio, Italy, Gabriele Bavota Software Institute, USI Università della Svizzera italiana Pre-print File Attached | ||
11:18 12mTalk | How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs Journal-first Papers Rahul Yedida , Hong Jin Kang UCLA, Huy Tu North Carolina State University, USA, Xueqi Yang NCSU, David Lo Singapore Management University, Tim Menzies North Carolina State University Link to publication DOI Authorizer link Pre-print | ||
11:30 12mTalk | Polyglot Code Smell Detection for Infrastructure as Code with GLITCH Tool Demonstrations Nuno Saavedra INESC-ID and IST, University of Lisbon, João Gonçalves INESC-ID and IST, University of Lisbon, Miguel Henriques INESC-ID and IST, University of Lisbon, João F. Ferreira INESC-ID and IST, University of Lisbon, Alexandra Mendes Faculty of Engineering, University of Porto & INESC TEC Pre-print File Attached | ||
11:42 12mTalk | Enhancing the defectiveness prediction of methods and classes via JIT Journal-first Papers Falessi Davide University of Rome Tor Vergata, Simone Mesiano Laureani University of Rome Tor Vergata, Jonida Çarka University of Rome Tor Vergata, Matteo Esposito University of Rome Tor Vergata, Daniel Alencar Da Costa University of Otago Link to publication DOI File Attached |