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Miguel Henriques

dblp:355/0428 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%
Network and information security
1 paper
Systems and software security · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution › code smell
code smell detection
0.712023
Polyglot Code Smell Detection for Infrastructure as Code with GLITCH · ASE 2023
Software maintenance and evolution › devops
infrastructure as code
0.712023
Polyglot Code Smell Detection for Infrastructure as Code with GLITCH · ASE 2023
Systems and software security
configuration security
0.212023
Polyglot Code Smell Detection for Infrastructure as Code with GLITCH · ASE 2023

Methods — techniques the papers use, named apart from their topics

intermediate representation · 1.3
YearPublicationVenuePosition
2023 Polyglot Code Smell Detection for Infrastructure as Code with GLITCH
abstract
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.
Nuno Saavedra, Miguel Henriques, João F. Ferreira 0001, Alexandra Mendes
ASE3