Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

2.1K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
2.1K
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.8K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.8K
Structural Classification of Joints01:20

Structural Classification of Joints

3.8K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
3.8K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

147
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
147
Language Development01:22

Language Development

434
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
434
Language and Cognition01:27

Language and Cognition

415
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
415

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Emerging evidence on the safety of enteral feeding during PRBC transfusion in preterm infants.

Pediatric research·2026
Same author

Emerging role of artificial intelligence in necrotizing enterocolitis and implementation challenges.

Pediatric research·2026
Same author

Med-ViX-Ray: Enhancing explainable chest X-ray analysis with clinical knowledge graphs.

Computer methods and programs in biomedicine·2026
Same author

A Pathophysiological Approach for Early Detection and Prevention of AKI in the NICU.

American journal of perinatology·2026
Same author

Zymoseptoria tritici stealth infection is facilitated by stage-specific downregulation of a β-glucanase.

The New phytologist·2025
Same author

Adding value to botanical resources: Metabolic network analysis along with high-resolution bioassays screening and UHPLC-qToF-high-resolution MS/MS profiling detail the pharmacological potential of underexplored Latin-American plants.

Fitoterapia·2025

Related Experiment Video

Updated: Aug 27, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

673

FindICI: Using machine learning to detect linguistic inconsistencies between code and natural language descriptions

Nemania Borovits1, Indika Kumara1, Dario Di Nucci2

  • 1Jheronimus Academy of Data Science, Tilburg University, Tilburg, The Netherlands.

Empirical Software Engineering
|September 26, 2022
PubMed
Summary

This study introduces FindICI, an automated method to detect linguistic anti-patterns in Infrastructure-as-Code (IaC) scripts. It identifies inconsistencies between code logic and names, improving code quality and maintainability.

Keywords:
Deep learningInfrastructure as codeLinguistic anti-patternsMachine learningWord embedding

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

444
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

538

Related Experiment Videos

Last Updated: Aug 27, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

673
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

444
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

538

Area of Science:

  • Software Engineering
  • Computer Science

Background:

  • Linguistic anti-patterns, such as naming inconsistencies, degrade source code quality.
  • Infrastructure-as-Code (IaC) scripts require high readability and maintainability for effective environment management.

Purpose of the Study:

  • To develop and evaluate an automated approach for detecting linguistic anti-patterns in IaC scripts.
  • Specifically, to identify inconsistencies between the implementation (body) and naming (short text names) of IaC code units.

Main Methods:

  • Proposing FindICI, a novel approach utilizing word embedding and classification algorithms.
  • Generating code embeddings from the abstract syntax tree (AST) of IaC code units.
  • Employing machine learning techniques, including classical and deep learning models, for inconsistency detection.

Main Results:

  • Evaluated FindICI on Ansible tasks extracted from open-source repositories.
  • Demonstrated comparable and satisfactory performance across various word embedding models and classification algorithms.
  • Successfully detected inconsistent Ansible tasks, particularly for frequently used Ansible modules.

Conclusions:

  • FindICI effectively detects linguistic anti-patterns in IaC scripts.
  • The proposed method enhances the maintainability and understandability of IaC code.
  • Automated detection of these anti-patterns is feasible and beneficial for managing computing environments.