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

Distribution Reliability and Automation01:25

Distribution Reliability and Automation

129
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...
129
Quality Assurance01:19

Quality Assurance

155
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
155
Vebe Test01:22

Vebe Test

173
The Vebe test is a method used to measure the workability of concrete, particularly effective for dry concrete mixes. This test employs a specific apparatus that includes a cylindrical chamber, a standard slump cone, and a transparent disc-shaped rider, all mounted on a vibrating table. The cylindrical chamber has dimensions of nine and a half inches in diameter and eight inches in height.
To conduct the test, concrete is placed into the slump cone. The concrete is filled in layers and...
173
Electro-mechanical Systems01:19

Electro-mechanical Systems

1.0K
Electromechanical systems are intricate configurations that effectively combine electrical and mechanical elements to achieve a desired outcome. Central to many of these systems is the DC motor, a device that converts electrical energy into mechanical motion, enabling various applications ranging from simple fans to complex robotic mechanisms.
A key component of the DC motor is the armature, a rotating circuit positioned within a magnetic field. As an electric current passes through the...
1.0K
Testing Water Quality01:14

Testing Water Quality

135
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
135
Econometric Views (EViews)01:29

Econometric Views (EViews)

167
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
167

You might also read

Related Articles

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

Sort by
Same author

Tools and benchmarks evolve: what is their impact on parameter tuning in SBSE experiments?

Empirical software engineering·2025
Same author

Causes and effects of fitness landscapes in system test generation: a replication study.

Automated software engineering·2025
Same author

Enhanced visibility graph for EEG classification.

Frontiers in neuroscience·2025
Same author

Ensemble fuzzy deep learning for brain tumor detection.

Scientific reports·2025
Same author

Technology adoption performance evaluation applied to testing industrial REST APIs.

Automated software engineering·2024
Same author

Tool report: EvoMaster-black and white box search-based fuzzing for REST, GraphQL and RPC APIs.

Automated software engineering·2024
Same journal

A family of experiments about how developers perceive delayed system response time.

Software quality journal·2024
Same journal

Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system.

Software quality journal·2024
Same journal

Editorial.

Software quality journal·2024
Same journal

Machine learning for mHealth apps quality evaluation: An approach based on user feedback analysis.

Software quality journal·2024
Same journal

An empirical investigation on the challenges of creating custom static analysis rules for defect localization.

Software quality journal·2024
See all related articles

Related Experiment Video

Updated: Jul 16, 2025

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER
07:26

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

12.1K

Building an open-source system test generation tool: lessons learned and empirical analyses with EvoMaster.

Andrea Arcuri1,2, Man Zhang1, Asma Belhadi1

  • 1Kristiania University College, Oslo, Norway.

Software Quality Journal
|September 11, 2023
PubMed
Summary
This summary is machine-generated.

Developing AI-driven software testing tools presents unique challenges, especially for academic researchers. This paper shares experiences building the EvoMaster tool to aid the research community and improve industrial software testing practices.

Keywords:
ExperimentationFuzzingSBSTSoftware testingTool

More Related Videos

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.5K
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.2K

Related Experiment Videos

Last Updated: Jul 16, 2025

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER
07:26

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

12.1K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.5K
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.2K

Area of Science:

  • Computer Science
  • Software Engineering
  • Artificial Intelligence

Background:

  • Software testing research frequently requires developing prototype tools.
  • Researchers, often lacking industrial experience, face development, use, and verification challenges.
  • Specific issues arise with AI techniques like evolutionary algorithms due to their inherent randomness.

Purpose of the Study:

  • To report on the experience of building the open-source EvoMaster tool for system-level test case generation.
  • To provide concrete solutions for common development challenges in research software prototypes.
  • To boost the research community and increase the impact of scientific research on industrial practice.

Main Methods:

  • Development of the open-source EvoMaster tool.
  • Application of AI-based techniques, specifically evolutionary algorithms, for test case generation.
  • Addressing challenges related to software scaffolding for efficient experiment execution.

Main Results:

  • Identification of specific challenges in developing and verifying software testing prototypes.
  • Successful development of the EvoMaster tool for enterprise application system-level test case generation.
  • Experience gained in managing the randomness of AI techniques in empirical studies.

Conclusions:

  • Sharing practical experience in building research prototypes can significantly benefit the software testing research community.
  • Addressing development challenges proactively leads to more robust and impactful research tools.
  • Improved research prototypes can bridge the gap between scientific advancements and industrial software testing practices.